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Sample records for s1for acetyl-group recognition

  1. The Recognition Unit of FIBCD1 Organizes into a Noncovalently Linked Tetrameric Structure and Uses a Hydrophobic Funnel (S1) for Acetyl Group Recognition*

    PubMed Central

    Thomsen, Theresa; Moeller, Jesper B.; Schlosser, Anders; Sorensen, Grith L.; Moestrup, Soren K.; Palaniyar, Nades; Wallis, Russell; Mollenhauer, Jan; Holmskov, Uffe

    2010-01-01

    We have recently identified FIBCD1 (Fibrinogen C domain containing 1) as a type II transmembrane endocytic receptor located primarily in the intestinal brush border. The ectodomain of FIBCD1 comprises a coiled coil, a polycationic region, and a C-terminal FReD (fibrinogen-related domain) that assembles into disulfide-linked homotetramers. The FIBCD1-FReD binds Ca2+ dependently to acetylated structures like chitin, N-acetylated carbohydrates, and amino acids. FReDs are present in diverse innate immune pattern recognition proteins including the ficolins and horseshoe crab TL5A. Here, we use chemical cross-linking, combined with analytical ultracentrifugation and electron microscopy of the negatively stained recombinant FIBCD1-FReD to show that it assembles into noncovalent tetramers in the absence of the coiled coil. We use surface plasmon resonance, carbohydrate binding, and pulldown assays combined with site-directed mutagenesis to define the binding site involved in the interaction of FIBCD1 with acetylated structures. We show that mutations of central residues (A432V and H415G) in the hydrophobic funnel (S1) abolish the binding of FIBCD1 to acetylated bovine serum albumin and chitin. The double mutations (D393N/D395A) at the putative calcium-binding site reduce the ability of FIBCD1 to bind ligands. We conclude that the FReDs of FIBCD1 forms noncovalent tetramers and that the acetyl-binding site of FReDs of FIBCD1 is homologous to that of tachylectin 5A and M-ficolin but not to the FReD of L-ficolin. We suggest that the spatial organization of the FIBCD1-FReDs determine the molecular pattern recognition specificity and subsequent biological functions. PMID:19892701

  2. The recognition unit of FIBCD1 organizes into a noncovalently linked tetrameric structure and uses a hydrophobic funnel (S1) for acetyl group recognition.

    PubMed

    Thomsen, Theresa; Moeller, Jesper B; Schlosser, Anders; Sorensen, Grith L; Moestrup, Soren K; Palaniyar, Nades; Wallis, Russell; Mollenhauer, Jan; Holmskov, Uffe

    2010-01-01

    We have recently identified FIBCD1 (Fibrinogen C domain containing 1) as a type II transmembrane endocytic receptor located primarily in the intestinal brush border. The ectodomain of FIBCD1 comprises a coiled coil, a polycationic region, and a C-terminal FReD (fibrinogen-related domain) that assembles into disulfide-linked homotetramers. The FIBCD1-FReD binds Ca(2+) dependently to acetylated structures like chitin, N-acetylated carbohydrates, and amino acids. FReDs are present in diverse innate immune pattern recognition proteins including the ficolins and horseshoe crab TL5A. Here, we use chemical cross-linking, combined with analytical ultracentrifugation and electron microscopy of the negatively stained recombinant FIBCD1-FReD to show that it assembles into noncovalent tetramers in the absence of the coiled coil. We use surface plasmon resonance, carbohydrate binding, and pulldown assays combined with site-directed mutagenesis to define the binding site involved in the interaction of FIBCD1 with acetylated structures. We show that mutations of central residues (A432V and H415G) in the hydrophobic funnel (S1) abolish the binding of FIBCD1 to acetylated bovine serum albumin and chitin. The double mutations (D393N/D395A) at the putative calcium-binding site reduce the ability of FIBCD1 to bind ligands. We conclude that the FReDs of FIBCD1 forms noncovalent tetramers and that the acetyl-binding site of FReDs of FIBCD1 is homologous to that of tachylectin 5A and M-ficolin but not to the FReD of L-ficolin. We suggest that the spatial organization of the FIBCD1-FReDs determine the molecular pattern recognition specificity and subsequent biological functions. PMID:19892701

  3. Studies of conformation and interaction of the cyclohexenone and acetyl group of progesterone with liposomes.

    PubMed

    Sanchez-Bueno, A; Watanabe, S; Sancho, M J; Saito, T

    1991-02-01

    The conformations of the A-ring and the 17-acetyl groups of progesterone were examined within liposomes, which were prepared from L-alpha-phosphatidylcholine in the presence or absence of cholesterol in the buffer, using qualitative nuclear magnetic resonance and circular dichroism of the progesterone spectra in the wavelength regions of 260-360 nm. The preferred conformational assignments, in the rotational conformations of the 17-acetyl group and invertible conformations of the cyclohexenone of progesterone were discussed on the basis of the elliptical strength of the Cotton effect and an energy estimation of the preferred conformers. Energetically unstable conformers of the acetyl group and alpha,beta-unsaturated cyclohexenone of progesterone remarkably increased with an increase in the concentration of the liposomes. The liposomes containing 10% cholesterol were similar to the effect of the liposomes lacking cholesterol on the 17-acetyl group and the alpha,beta-unsaturated cyclohexenone but those containing 50% cholesterol showed an increase in the number of energetically stable conformers of the alpha,beta-unsaturated cyclohexenone. The nuclear magnetic resonance signal from liposomes together with the progesterone indicated the existence of the progesterone adjacent to a double bond or ester moiety in the lipid molecule. Therefore, it was apparent that the liposomes and the cholesterol within the liposomes regulated the conformational populations of both the cyclohexone and acetyl groups of the progesterone molecule. PMID:2004040

  4. Effect of Acetyl Group on Mechanical Properties of Chitin/Chitosan Nanocrystal: A Molecular Dynamics Study

    PubMed Central

    Cui, Junhe; Yu, Zechuan; Lau, Denvid

    2016-01-01

    Chitin fiber is the load-bearing component in natural chitin-based materials. In these materials, chitin is always partially deacetylated to different levels, leading to diverse material properties. In order to understand how the acetyl group enhances the fracture resistance capability of chitin fiber, we constructed atomistic models of chitin with varied acetylation degree and analyzed the hydrogen bonding pattern, fracture, and stress-strain behavior of these models. We notice that the acetyl group can contribute to the formation of hydrogen bonds that can stabilize the crystalline structure. In addition, it is found that the specimen with a higher acetylation degree presents a greater resistance against fracture. This study describes the role of the functional group, acetyl groups, in crystalline chitin. Such information could provide preliminary understanding of nanomaterials when similar functional groups are encountered. PMID:26742033

  5. The acetyl group deficit at the onset of contraction in ischaemic canine skeletal muscle.

    PubMed

    Roberts, Paul A; Loxham, Susan J G; Poucher, Simon M; Constantin-Teodosiu, Dumitru; Greenhaff, Paul L

    2002-10-15

    Considerable debate surrounds the identity of the precise cellular site(s) of inertia that limit the contribution of mitochondrial ATP resynthesis towards a step increase in workload at the onset of muscular contraction. By detailing the relationship between canine gracilis muscle energy metabolism and contractile function during constant-flow ischaemia, in the absence (control) and presence of pyruvate dehydrogenase complex activation by dichloroacetate, the present study examined whether there is a period at the onset of contraction when acetyl-coenzyme A (acetyl-CoA) availability limits mitochondrial ATP resynthesis, i.e. whether a limitation in mitochondrial acetyl group provision exists. Secondly, assuming it does exist, we also aimed to identify the mechanism by which dichloroacetate overcomes this "acetyl group deficit". No increase in pyruvate dehydrogenase complex activation or acetyl group availability occurred during the first 20 s of contraction in the control condition, with strong trends for both acetyl-CoA and acetylcarnitine to actually decline (indicating the existence of an acetyl group deficit). Dichloroacetate increased resting pyruvate dehydrogenase complex activation, acetyl-CoA and acetylcarnitine by approximately 20-fold (P < 0.01), approximately 3-fold (P < 0.01) and approximately 4-fold (P < 0.01), respectively, and overcame the acetyl group deficit at the onset of contraction. As a consequence, the reliance upon non-oxidative ATP resynthesis was reduced by approximately 40 % (P < 0.01) and tension development was increased by approximately 20 % (P < 0.05) following 5 min of contraction. The present study has demonstrated, for the first time, the existence of an acetyl group deficit at the onset of contraction and has confirmed the metabolic and functional benefits to be gained from overcoming this inertia. PMID:12381829

  6. Catalytic Depolymerization of Chitin with Retention of N-Acetyl Group.

    PubMed

    Yabushita, Mizuho; Kobayashi, Hirokazu; Kuroki, Kyoichi; Ito, Shogo; Fukuoka, Atsushi

    2015-11-01

    Chitin, a polymer of N-acetylglucosamine units with β-1,4-glycosidic linkages, is the most abundant marine biomass. Chitin monomers containing N-acetyl groups are useful precursors to various fine chemicals and medicines. However, the selective conversion of robust chitin to N-acetylated monomers currently requires a large excess of acid or a long reaction time, which limits its application. We demonstrate a fast catalytic transformation of chitin to monomers with retention of N-acetyl groups by combining mechanochemistry and homogeneous catalysis. Mechanical-force-assisted depolymerization of chitin with a catalytic amount of H2SO4 gave soluble short-chain oligomers. Subsequent hydrolysis of the ball-milled sample provided N-acetylglucosamine in 53% yield, and methanolysis afforded 1-O-methyl-N-acetylglucosamine in yields of up to 70%. Our process can greatly reduce the use of acid compared to the conventional process. PMID:26538108

  7. Acetyl group availability influences phosphocreatine degradation even during intense muscle contraction.

    PubMed

    Timmons, James A; Constantin-Teodosiu, Dumitru; Poucher, Simon M; Greenhaff, Paul L

    2004-12-15

    We previously established that activation of the pyruvate dehydrogenase complex (PDC) using dichloroacetate (DCA) reduced the reliance on substrate-level phosphorylation (SLP) at the onset of exercise, with normal and reduced blood flow. PDC activation also reduced fatigue development during contraction with reduced blood flow. Since these observations, several studies have re-evaluated our observations. One study demonstrated a performance benefit without a reduction in SLP, raising a question mark over PDC's role in the regulation of ATP regeneration and our interpretation of fatigue mechanisms. Using a model of muscle contraction similar to the conflicting study (i.e. tetanic rather than twitch stimulation), we re-examined this question. Using canine skeletal muscle, one group was infused with saline while the other was pretreated with 300 mg (kg body mass)(-1) DCA. Muscle biopsies were taken at rest, peak tension (1 min) and after 6 min of tetanic electrical stimulation (75 ms on-925 ms off per second) and blood flow was limited to 25% of normal values observed during contraction. DCA reduced phosphocreatine (PCr) degradation by 40% during the first minute of contraction, but did not prevent the almost complete depletion of PCr stores at 6 min, while muscle fatigue did not differ between the two groups. During intermittent tetanic stimulation PCr degradation was 75% greater than with our previous 3 Hz twitch contraction protocol, despite a similar rate of oxygen consumption at 6 min. Thus, in the present study enhanced acetyl group availability altered the time course of PCr utilization but did not prevent the decline towards depletion. Consistent with our earlier conclusions, DCA pretreatment reduces muscle fatigue only when SLP is attenuated. The present study and our met-analysis indicates that enhanced acetyl group availability results in a readily measurable reduction in SLP when the initial rate of PCr utilization is approximately 1 mmol (kg dry mass)(-1

  8. Increased acetyl group availability enhances contractile function of canine skeletal muscle during ischemia.

    PubMed

    Timmons, J A; Poucher, S M; Constantin-Teodosiu, D; Worrall, V; Macdonald, I A; Greenhaff, P L

    1996-02-01

    Skeletal muscle contractile function is impaired during acute ischemia such as that experienced by peripheral vascular disease patients. We therefore, examined the effects of dichloroacetate, which can alter resting metabolism, on canine gracilis muscle contractile function during constant flow ischemia. Pretreatment with dichloroacetate increased resting pyruvate dehydrogenase complex activity and resting acetylcarnitine concentration by approximately 4- and approximately 10-fold, respectively. After 20-min contraction the control group had demonstrated an approximately 40% reduction in isomeric tension whereas the dichloroacetate group had fatigued by approximately 25% (P < 0.05). Dichloroacetate resulted in less lactate accumulation (10.3 +/- 3.0 vs 58.9 +/- 10.5 mmol.kg-1 dry muscle [dm], P < 0.05) and phosphocreatine hydrolysis (15.6 +/- 6.3 vs 33.8 +/- 9.0 mmol.kg-1 dm, P < 0.05) during contraction. Acetylcarnitine concentration fell during contraction by 5.4 +/- 1.8 mmol.kg-1 dm in the dichloroacetate group but increased by 10.0 +/- 1.9 mmol.kg-1 dm in the control group. In conclusion, dichloroacetate enhanced contractile function during ischemia, independently of blood flow, such that it appears oxidative ATP regeneration is limited by pyruvate dehydrogenase complex activity and acetyl group availability. PMID:8609248

  9. The Acetyl Group Buffering Action of Carnitine Acetyltransferase Offsets Macronutrient-induced Lysine Acetylation of Mitochondrial Proteins

    PubMed Central

    Davies, Michael N.; Kjalarsdottir, Lilja; Thompson, J. Will; Dubois, Laura G.; Stevens, Robert D.; Ilkayeva, Olga R.; Brosnan, M. Julia; Rolph, Timothy P.; Grimsrud, Paul A.; Muoio, Deborah M.

    2016-01-01

    Lysine acetylation (AcK), a posttranslational modification wherein a two-carbon acetyl group binds covalently to a lysine residue, occurs prominently on mitochondrial proteins and has been linked to metabolic dysfunction. An emergent theory suggests mitochondrial AcK occurs via mass action rather than targeted catalysis. To test this hypothesis we performed mass spectrometry-based acetylproteomic analyses of quadriceps muscles from mice with skeletal muscle-specific deficiency of carnitine acetyltransferase (CrAT), an enzyme that buffers the mitochondrial acetyl-CoA pool by converting short-chain acyl-CoAs to their membrane permeant acylcarnitine counterparts. CrAT deficiency increased tissue acetyl-CoA levels and susceptibility to diet-induced AcK of broad-ranging mitochondrial proteins, coincident with diminished whole body glucose control. Sub-compartment acetylproteome analyses of muscles from obese mice and humans showed remarkable overrepresentation of mitochondrial matrix proteins. These findings reveal roles for CrAT and L-carnitine in modulating the muscle acetylproteome and provide strong experimental evidence favoring the nonenzymatic carbon pressure model of mitochondrial AcK. PMID:26748706

  10. The effect of substitution of the N-acetyl groups of N-acetylgalactosamine residues in chondroitin sulfate on its degradation by chondroitinase ABC.

    PubMed

    Madhunapantula, Subbarao V; Achur, Rajeshwara N; Bhavanandan, Veer P; Gowda, D Channe

    2007-11-01

    Chondroitinase ABC is a lyase that degrades chondroitin sulfate, dermatan sulfate and hyaluronic acid into disaccharides. The purpose of this study was to determine the ability of chondroitinase ABC to degrade chondroitin sulfate in which the N-acetyl groups are substituted with different acyl groups. The bovine tracheal chondroitin sulfate A (bCSA) was N-deacetylated by hydrazinolysis, and the free amino groups derivatized into N-formyl, N-propionyl, N-butyryl, N-hexanoyl or N-benzoyl amides. Treatment of the N-acyl or N-benzoyl derivatives of bCSA with chondroitinase ABC and analysis of the products showed that the N-formyl, N-hexanoyl and N-benzoyl derivatives are completely resistant to the enzyme. In contrast, the N-propionyl or N-butyryl derivatives were degraded into disaccharides with slower kinetics compared to that of unmodified bCSA. The rate of degradation of bCSA derivatives by the enzyme was found to be in the order of N-acetyl>N-propionyl>N-butyryl bCSA. These results have important implications for understanding the interaction of N-acetyl groups of glycosaminoglycans with chondroitinase ABC. PMID:17533514

  11. Application of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in preparation of chitosan oligosaccharides (COS) with degree of polymerization (DP) 5-12 containing well-distributed acetyl groups

    NASA Astrophysics Data System (ADS)

    Chen, Mian; Zhu, Xiqiang; Li, Zhiming; Guo, Xueping; Ling, Peixue

    2010-02-01

    COS have many biological activities, and have been widely used as a health food. Molecular size is considered as a key parameter for COS' activities. However, many criteria are used practically, and true qualities of COS from different producers may not be always comparable. This can partly explain the disagreement in COS' functional researches, as resulting in COS, even with astonish effects, have not been further developed as a drug for tumor patients. As anti-tumor activities have been studied based on DP in pharmacological researches, we employed MALDI-TOF-MS to monitor fine structure, including DP, in COS' preparation and comparison. Then one of the COS products was analyzed with the composition of DP 5-12, mainly 7-10. Moreover, that COS' product contains well-distributed acetyl groups, while typical Commercial COS sample nearly contains no acetyl groups. As fresh precise parameters, the DP and the number of acetyl groups matching with special DP can be introduced in COS' further study on structure-activity relationships (SARs) as a new drug.

  12. Voice recognition.

    PubMed

    Mehta, Amit; McLoud, Theresa C

    2003-07-01

    Voice recognition represents one of the new technologies that are changing the practice of radiology. Thirty percent of radiology practices are either currently or plan to have voice recognition (VR) systems. VR software encompasses 4 core processes: spoken recognition of human speech, synthesis of human readable characters into speech, speaker identification and verification, and comprehension. Many software packages are available offering VR. All these packages should contain an interface with the radiology information system. The benefits include decreased turnaround time and cost savings. Its advantages include the transfer of secretarial duties to the radiologist with a result in decreased productivity. PMID:12867815

  13. Speech recognition based on pattern recognition techniques

    NASA Astrophysics Data System (ADS)

    Rabiner, Lawrence R.

    1990-05-01

    Algorithms for speech recognition can be characterized broadly as pattern recognition approaches and acoustic phonetic approaches. To date, the greatest degree of success in speech recognition has been obtained using pattern recognition paradigms. The use of pattern recognition techniques were applied to the problems of isolated word (or discrete utterance) recognition, connected word recognition, and continuous speech recognition. It is shown that understanding (and consequently the resulting recognizer performance) is best to the simplest recognition tasks and is considerably less well developed for large scale recognition systems.

  14. Neoadjuvant short-course hyperfractionated accelerated radiotherapy (SC-HART) combined with S-1 for locally advanced rectal cancer.

    PubMed

    Doi, Hiroshi; Beppu, Naohito; Odawara, Soichi; Tanooka, Masao; Takada, Yasuhiro; Niwa, Yasue; Fujiwara, Masayuki; Kimura, Fumihiko; Yanagi, Hidenori; Yamanaka, Naoki; Kamikonya, Norihiko; Hirota, Shozo

    2013-11-01

    The purpose of this study was to examine the safety and feasibility of a novel protocol of neoadjuvant short-course hyperfractionated accelerated radiotherapy (SC-HART) combined with S-1 for locally advanced rectal cancer. A total of 56 patients with lower rectal cancer of cT3N1M0 (Stage III b) was treated with SC-HART followed by radical surgery, and were analyzed in the present study. SC-HART was performed with a dose of 2.5 Gy twice daily, with an interval of at least 6 hours between fractions, up to a total dose of 25 Gy (25 Gy in 10 fractions for 5 days) combined with S-1 for 10 days. Radical surgery was performed within three weeks following the end of the SC-HART. The median age was 64.6 (range, 39-85) years. The median follow-up term was 16.3 (range, 2-53) months. Of the 56 patients, 53 (94.4%) had no apparent adverse events before surgery; 55 (98.2%) completed the full course of neoadjuvant therapy, while one patient stopped chemotherapy because of Grade 3 gastrointestinal toxicity (CTCAE v.3). The sphincter preservation rate was 94.6%. Downstaging was observed in 45 patients (80.4%). Adjuvant chemotherapy was administered to 43 patients (76.8%). The local control rate, disease-free survival rate and disease-specific survival rate were 100%, 91.1% and 100%, respectively. To conclude, SC-HART combined with S-1 for locally advanced rectal cancer was well tolerated and produced good short-term outcomes. SC-HART therefore appeared to have a good feasibility for use in further clinical trials. PMID:23658415

  15. Recognition intent and visual word recognition.

    PubMed

    Wang, Man-Ying; Ching, Chi-Le

    2009-03-01

    This study adopted a change detection task to investigate whether and how recognition intent affects the construction of orthographic representation in visual word recognition. Chinese readers (Experiment 1-1) and nonreaders (Experiment 1-2) detected color changes in radical components of Chinese characters. Explicit recognition demand was imposed in Experiment 2 by an additional recognition task. When the recognition was implicit, a bias favoring the radical location informative of character identity was found in Chinese readers (Experiment 1-1), but not nonreaders (Experiment 1-2). With explicit recognition demands, the effect of radical location interacted with radical function and word frequency (Experiment 2). An estimate of identification performance under implicit recognition was derived in Experiment 3. These findings reflect the joint influence of recognition intent and orthographic regularity in shaping readers' orthographic representation. The implication for the role of visual attention in word recognition was also discussed. PMID:19036609

  16. Recognition Tunneling

    PubMed Central

    Lindsay, Stuart; He, Jin; Sankey, Otto; Hapala, Prokop; Jelinek, Pavel; Zhang, Peiming; Chang, Shuai; Huang, Shuo

    2010-01-01

    Single molecules in a tunnel junction can now be interrogated reliably using chemically-functionalized electrodes. Monitoring stochastic bonding fluctuations between a ligand bound to one electrode and its target bound to a second electrode (“tethered molecule-pair” configuration) gives insight into the nature of the intermolecular bonding at a single molecule-pair level, and defines the requirements for reproducible tunneling data. Simulations show that there is an instability in the tunnel gap at large currents, and this results in a multiplicity of contacts with a corresponding spread in the measured currents. At small currents (i.e. large gaps) the gap is stable, and functionalizing a pair of electrodes with recognition reagents (the “free analyte” configuration) can generate a distinct tunneling signal when an analyte molecule is trapped in the gap. This opens up a new interface between chemistry and electronics with immediate implications for rapid sequencing of single DNA molecules. PMID:20522930

  17. Molecular mechanism underlying promiscuous polyamine recognition by spermidine acetyltransferase.

    PubMed

    Sugiyama, Shigeru; Ishikawa, Sae; Tomitori, Hideyuki; Niiyama, Mayumi; Hirose, Mika; Miyazaki, Yuma; Higashi, Kyohei; Murata, Michio; Adachi, Hiroaki; Takano, Kazufumi; Murakami, Satoshi; Inoue, Tsuyoshi; Mori, Yusuke; Kashiwagi, Keiko; Igarashi, Kazuei; Matsumura, Hiroyoshi

    2016-07-01

    Spermidine acetyltransferase (SAT) from Escherichia coli, which catalyses the transfer of acetyl groups from acetyl-CoA to spermidine, is a key enzyme in controlling polyamine levels in prokaryotic cells. In this study, we determined the crystal structure of SAT in complex with spermidine (SPD) and CoA at 2.5Å resolution. SAT is a dodecamer organized as a hexamer of dimers. The secondary structural element and folding topology of the SAT dimer resemble those of spermidine/spermine N(1)-acetyltransferase (SSAT), suggesting an evolutionary link between SAT and SSAT. However, the polyamine specificity of SAT is distinct from that of SSAT and is promiscuous. The SPD molecule is also located at the inter-dimer interface. The distance between SPD and CoA molecules is 13Å. A deep, highly acidic, water-filled cavity encompasses the SPD and CoA binding sites. Structure-based mutagenesis and in-vitro assays identified SPD-bound residues, and the acidic residues lining the walls of the cavity are mostly essential for enzymatic activities. Based on mutagenesis and structural data, we propose an acetylation mechanism underlying promiscuous polyamine recognition for SAT. PMID:27163532

  18. Crystal structure of the tetrameric fibrinogen-like recognition domain of fibrinogen C domain containing 1 (FIBCD1) protein.

    PubMed

    Shrive, Annette K; Moeller, Jesper B; Burns, Ian; Paterson, Jenny M; Shaw, Amy J; Schlosser, Anders; Sorensen, Grith L; Greenhough, Trevor J; Holmskov, Uffe

    2014-01-31

    The high resolution crystal structures of a recombinant fragment of the C-terminal fibrinogen-like recognition domain of FIBCD1, a vertebrate receptor that binds chitin, have been determined. The overall tetrameric structure shows similarity in structure and aggregation to the horseshoe crab innate immune protein tachylectin 5A. The high affinity ligand N-acetylmannosamine (ManNAc) binds in the S1 site, predominantly via the acetyl group with the oxygen and acetamide nitrogen hydrogen-bonded to the protein and the methyl group inserted into a hydrophobic pocket. The binding of the ManNAc pyranose ring differs markedly between the two independent subunits, but in all structures the binding of the N-acetyl group is conserved. In the native structure, a crystal contact results in one of the independent protomers binding the first GlcNAc of the Asn(340) N-linked glycan on the other independent protomer. In the ligand-bound structure this GlcNAc is replaced by the higher affinity ligand ManNAc. In addition, a sulfate ion has been modeled into the electron density at a location similar to the S3 binding site in L-ficolin, whereas in the native structure an acetate ion has been placed in the S1 N-acetyl binding site, and a sulfate ion has been placed adjacent to this site. These ion binding sites are ideally placed to receive the N-acetyl and sulfate groups of sulfated GalNAc residues of glycosaminoglycans such as chondroitin and dermatan sulfate. Together, these structures give insight into important determinants of ligand selectivity, demonstrating versatility in recognition and binding while maintaining conservation in N-acetyl and calcium binding. PMID:24293368

  19. Speech recognition and understanding

    SciTech Connect

    Vintsyuk, T.K.

    1983-05-01

    This article discusses the automatic processing of speech signals with the aim of finding a sequence of works (speech recognition) or a concept (speech understanding) being transmitted by the speech signal. The goal of the research is to develop an automatic typewriter that will automatically edit and type text under voice control. A dynamic programming method is proposed in which all possible class signals are stored, after which the presented signal is compared to all the stored signals during the recognition phase. Topics considered include element-by-element recognition of words of speech, learning speech recognition, phoneme-by-phoneme speech recognition, the recognition of connected speech, understanding connected speech, and prospects for designing speech recognition and understanding systems. An application of the composition dynamic programming method for the solution of basic problems in the recognition and understanding of speech is presented.

  20. Survey of Gait Recognition

    NASA Astrophysics Data System (ADS)

    Liu, Ling-Feng; Jia, Wei; Zhu, Yi-Hai

    Gait recognition, the process of identifying an individual by his /her walking style, is a relatively new research area. It has been receiving wide attention in the computer vision community. In this paper, a comprehensive survey of video based gait recognition approaches is presented. And the research challenges and future directions of the gait recognition are also discussed.

  1. Optical Pattern Recognition

    NASA Astrophysics Data System (ADS)

    Yu, Francis T. S.; Jutamulia, Suganda

    2008-10-01

    Contributors; Preface; 1. Pattern recognition with optics Francis T. S. Yu and Don A. Gregory; 2. Hybrid neural networks for nonlinear pattern recognition Taiwei Lu; 3. Wavelets, optics, and pattern recognition Yao Li and Yunglong Sheng; 4. Applications of the fractional Fourier transform to optical pattern recognition David Mendlovic, Zeev Zalesky and Haldum M. Oxaktas; 5. Optical implementation of mathematical morphology Tien-Hsin Chao; 6. Nonlinear optical correlators with improved discrimination capability for object location and recognition Leonid P. Yaroslavsky; 7. Distortion-invariant quadratic filters Gregory Gheen; 8. Composite filter synthesis as applied to pattern recognition Shizhou Yin and Guowen Lu; 9. Iterative procedures in electro-optical pattern recognition Joseph Shamir; 10. Optoelectronic hybrid system for three-dimensional object pattern recognition Guoguang Mu, Mingzhe Lu and Ying Sun; 11. Applications of photrefractive devices in optical pattern recognition Ziangyang Yang; 12. Optical pattern recognition with microlasers Eung-Gi Paek; 13. Optical properties and applications of bacteriorhodopsin Q. Wang Song and Yu-He Zhang; 14. Liquid-crystal spatial light modulators Aris Tanone and Suganda Jutamulia; 15. Representations of fully complex functions on real-time spatial light modulators Robert W. Cohn and Laurence G. Hassbrook; Index.

  2. Diagnostic odor recognition

    PubMed

    Rosenblatt; Phan; Desandre; Lobon; Hsu

    2000-10-01

    Many diseases, toxic ingestions, and intoxications have characteristic odors. These odors may provide diagnostic clues that affect rapid treatment long before laboratory confirmation or clinical deterioration. Odor recognition skills, similar to auscultation and palpation skills, require teaching and practical exposure. Dr. Goldfrank and colleagues recognized the importance of teaching odor recognition to emergency service providers. They proposed the "sniffing bar" method for odor recognition training. OBJECTIVES: (1) To identify the recognition rates of medically important odors among emergency care providers. (2) To investigate the effectiveness of teaching odor recognition. Hypothesis: The recognition rates of medically important odors will increase after teaching exposure. METHODS: The study exposed emergency care providers to 11 tubes of odors. Identifications of each substance were recorded. After corrective feedback, subjects were re-tested on their ability to identify the odors. Analysis of odor recognition improvement after teaching was done via chi-square test. RESULTS: Improvement in identification after teaching was seen in all odors. However, the improvement was significant only in the lesscommon substances because their initial recognition was especially low. Significant changes may improve with a larger sample size. Subjects often confuse the odors of alcohol with acetone, and wintergreen with camphor. CONCLUSIONS: The recognition rates are higher for the more-common odors, and lower for the less-common odors. Teaching exposures to the less well-known odors are effective and can significantly improve the recognition rate of these substances. Because odor recognition may affect rapid diagnosis and treatment of certain medical emergencies such as toxic ingestion, future studies should investigate the correlation between odor recognition and the ability to identify corresponding medical emergencies. PMID:11015270

  3. Moreland Recognition Program.

    ERIC Educational Resources Information Center

    Moreland Elementary School District, San Jose, CA.

    THE FOLLOWING IS THE FULL TEXT OF THIS DOCUMENT: Recognition for special effort and achievement has been noted as a component of effective schools. Schools in the Moreland School District have effectively improved standards of discipline and achievement by providing forty-six different ways for children to receive positive recognition. Good…

  4. CASE Recognition Awards.

    ERIC Educational Resources Information Center

    Currents, 1985

    1985-01-01

    A total of 294 schools, colleges, and universities received prizes in this year's CASE Recognition program. Awards were given in: public relations programs, student recruitment, marketing, program pulications, news writing, fund raising, radio programming, school periodicals, etc. (MLW)

  5. Planfulness and Recognition Memory

    ERIC Educational Resources Information Center

    Rogoff, Barbara; And Others

    1974-01-01

    A study of recorded and analyzed inspection times in a picture recognition memory task involving three different delays between inspection and test. Subjects were 108 4-, 6-, and 8-year-old children. (Author/SDH)

  6. Pattern recognition technique

    NASA Technical Reports Server (NTRS)

    Hong, J. P.

    1971-01-01

    Technique operates regardless of pattern rotation, translation or magnification and successfully detects out-of-register patterns. It improves accuracy and reduces cost of various optical character recognition devices and page readers and provides data input to computer.

  7. Context based gait recognition

    NASA Astrophysics Data System (ADS)

    Bazazian, Shermin; Gavrilova, Marina

    2012-06-01

    Gait recognition has recently become a popular topic in the field of biometrics. However, the main hurdle is the insufficient recognition rate in the presence of low quality samples. The main focus of this paper is to investigate how the performance of a gait recognition system can be improved using additional information about behavioral patterns of users and the context in which samples have been taken. The obtained results show combining the context information with biometric data improves the performance of the system at a very low cost. The amount of improvement depends on the distinctiveness of the behavioral patterns and the quality of the gait samples. Using the appropriate distinctive behavioral models it is possible to achieve a 100% recognition rate.

  8. Cartographic Character Recognition

    NASA Astrophysics Data System (ADS)

    Rafal, Howard B.; Ward, Matthew O.

    1989-11-01

    This work details a methodology for recognizing text elements on cartographic documents. Cartographic Character Recognition differs from traditional OCR in that many fonts may occur on the same page, text may have any orientation, text may follow a curved path, and text may be interfered with by graphics. The technique presented reduces the process to three steps: blobbing, stringing, and recognition. Blobbing uses image processing techniques to turn the gray level image into a binary image and then separates the image into probable graphic elements and probable text elements. Stringing relates the text elements into words. This is done by using proximity information of the letters to create string contours. These contours also help to retrieve orientation information of the text element. Recognition takes the strings and associates a letter with each blob. The letters are first approximated using feature descriptions, resulting in a set of possible letters. Orientation information is then used to refine the guesses. Final recognition is performed using elastic matching Feedback is employed at all phases of execution to refine the processing. Stringing and recognition give information that is useful in finding hidden blobs. Recognition helps make decisions about string paths. Results of this work are shown.

  9. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 8 Aliens and Nationality 1 2014-01-01 2014-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2... REPRESENTATION AND APPEARANCES § 292.2 Organizations qualified for recognition; requests for...

  10. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 8 Aliens and Nationality 1 2011-01-01 2011-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2... REPRESENTATION AND APPEARANCES § 292.2 Organizations qualified for recognition; requests for...

  11. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 8 Aliens and Nationality 1 2012-01-01 2012-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2... REPRESENTATION AND APPEARANCES § 292.2 Organizations qualified for recognition; requests for...

  12. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 8 Aliens and Nationality 1 2013-01-01 2013-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2... REPRESENTATION AND APPEARANCES § 292.2 Organizations qualified for recognition; requests for...

  13. 8 CFR 292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 8 Aliens and Nationality 1 2010-01-01 2010-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 292.2... REPRESENTATION AND APPEARANCES § 292.2 Organizations qualified for recognition; requests for...

  14. Probabilistic Open Set Recognition

    NASA Astrophysics Data System (ADS)

    Jain, Lalit Prithviraj

    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the "known unknowns". However, a proper open set recognition algorithm is needed to reduce the risk from the "unknown unknowns". This dissertation examines this concept and finds existing probabilistic multi-class recognition approaches are ineffective for true open set recognition. We hypothesize the cause is due to weak adhoc assumptions combined with closed-world assumptions made by existing calibration techniques. Intuitively, if we could accurately model just the positive data for any known class without overfitting, we could reject the large set of unknown classes even under this assumption of incomplete class knowledge. For this, we formulate the problem as one of modeling positive training data by invoking statistical extreme value theory (EVT) near the decision boundary of positive data with respect to negative data. We provide a new algorithm called the PI-SVM for estimating the unnormalized posterior probability of class inclusion. This dissertation also introduces a new open set recognition model called Compact Abating Probability (CAP), where the probability of class membership decreases in value (abates) as points move from known data toward open space. We show that CAP models improve open set recognition for multiple algorithms. Leveraging the CAP formulation, we go on to describe the novel Weibull-calibrated SVM (W-SVM) algorithm, which combines the useful properties of statistical EVT for score calibration with one-class and binary

  15. Automatic object recognition

    NASA Technical Reports Server (NTRS)

    Ranganath, H. S.; Mcingvale, Pat; Sage, Heinz

    1988-01-01

    Geometric and intensity features are very useful in object recognition. An intensity feature is a measure of contrast between object pixels and background pixels. Geometric features provide shape and size information. A model based approach is presented for computing geometric features. Knowledge about objects and imaging system is used to estimate orientation of objects with respect to the line of sight.

  16. Pattern recognition in bioinformatics.

    PubMed

    de Ridder, Dick; de Ridder, Jeroen; Reinders, Marcel J T

    2013-09-01

    Pattern recognition is concerned with the development of systems that learn to solve a given problem using a set of example instances, each represented by a number of features. These problems include clustering, the grouping of similar instances; classification, the task of assigning a discrete label to a given instance; and dimensionality reduction, combining or selecting features to arrive at a more useful representation. The use of statistical pattern recognition algorithms in bioinformatics is pervasive. Classification and clustering are often applied to high-throughput measurement data arising from microarray, mass spectrometry and next-generation sequencing experiments for selecting markers, predicting phenotype and grouping objects or genes. Less explicitly, classification is at the core of a wide range of tools such as predictors of genes, protein function, functional or genetic interactions, etc., and used extensively in systems biology. A course on pattern recognition (or machine learning) should therefore be at the core of any bioinformatics education program. In this review, we discuss the main elements of a pattern recognition course, based on material developed for courses taught at the BSc, MSc and PhD levels to an audience of bioinformaticians, computer scientists and life scientists. We pay attention to common problems and pitfalls encountered in applications and in interpretation of the results obtained. PMID:23559637

  17. 1987 CASE Recognition Awards.

    ERIC Educational Resources Information Center

    Currents, 1987

    1987-01-01

    The 1987 CASE Recognition Awards are presented for: general excellence in programs; student recruitment marketing improvement; video public service announcements, news, and commercial spots; total publications; magazines of the decade; improvement in periodicals; photocommunications via print; designer of the year and series; and imagination in…

  18. Microprocessor for speech recognition

    SciTech Connect

    Ishizuka, H.; Watari, M.; Sakoe, H.; Chiba, S.; Iwata, T.; Matsuki, T.; Kawakami, Y.

    1983-01-01

    A new single-chip microprocessor for speech recognition has been developed utilizing multi-processor architecture and pipelined structure. By DP-matching algorithm, the processor recognizes up to 340 isolated words or 40 connected words in realtime. 6 references.

  19. Automated galaxy recognition

    NASA Astrophysics Data System (ADS)

    Rappaport, Barry; Anderson, Kurt

    Previous approaches to automated image processing have used both deterministic and nondeterministic techniques. These have not used any form of conceptual learning nor have they employed artificial intelligence techniques. Addition of such techniques to the task of image processing may significantly enhance the efficiencies and accuracies of the recognition and classification processes. In our application, the objects to be recognized and classified are galaxies.

  20. View Invariant Gait Recognition

    NASA Astrophysics Data System (ADS)

    Seely, Richard D.; Goffredo, Michela; Carter, John N.; Nixon, Mark S.

    Recognition by gait is of particular interest since it is the biometric that is available at the lowest resolution, or when other biometrics are (intentionally) obscured. Gait as a biometric has now shown increasing recognition capability. There are many approaches and these show that recognition can achieve excellent performance on current large databases. The majority of these approaches are planar 2D, largely since the early large databases featured subjects walking in a plane normal to the camera view. To extend deployment capability, we need viewpoint invariant gait biometrics. We describe approaches where viewpoint invariance is achieved by 3D approaches or in 2D. In the first group, the identification relies on parameters extracted from the 3D body deformation during walking. These methods use several video cameras and the 3D reconstruction is achieved after a camera calibration process. On the other hand, the 2D gait biometric approaches use a single camera, usually positioned perpendicular to the subject’s walking direction. Because in real surveillance scenarios a system that operates in an unconstrained environment is necessary, many of the recent gait analysis approaches are orientated toward view-invariant gait recognition.

  1. Intralist Cueing of Recognition

    ERIC Educational Resources Information Center

    Slamecka, Norman J.

    1975-01-01

    Two experiments tested for effects of intralist cues upon recognition probability. Categorized and random lists were each tested, with targets appearing with zero, one or three intralist cues. Experiments showed substantial effects of trials and list type, but not of intralist context. (CHK)

  2. Optical Character Recognition.

    ERIC Educational Resources Information Center

    Converso, L.; Hocek, S.

    1990-01-01

    This paper describes computer-based optical character recognition (OCR) systems, focusing on their components (the computer, the scanner, the OCR, and the output device); how the systems work; and features to consider in selecting a system. A list of 26 questions to ask to evaluate systems for potential purchase is included. (JDD)

  3. Whole-book recognition.

    PubMed

    Xiu, Pingping; Baird, Henry S

    2012-12-01

    Whole-book recognition is a document image analysis strategy that operates on the complete set of a book's page images using automatic adaptation to improve accuracy. We describe an algorithm which expects to be initialized with approximate iconic and linguistic models--derived from (generally errorful) OCR results and (generally imperfect) dictionaries--and then, guided entirely by evidence internal to the test set, corrects the models which, in turn, yields higher recognition accuracy. The iconic model describes image formation and determines the behavior of a character-image classifier, and the linguistic model describes word-occurrence probabilities. Our algorithm detects "disagreements" between these two models by measuring cross entropy between 1) the posterior probability distribution of character classes (the recognition results resulting from image classification alone) and 2) the posterior probability distribution of word classes (the recognition results from image classification combined with linguistic constraints). We show how disagreements can identify candidates for model corrections at both the character and word levels. Some model corrections will reduce the error rate over the whole book, and these can be identified by comparing model disagreements, summed across the whole book, before and after the correction is applied. Experiments on passages up to 180 pages long show that when a candidate model adaptation reduces whole-book disagreement, it is also likely to correct recognition errors. Also, the longer the passage operated on by the algorithm, the more reliable this adaptation policy becomes, and the lower the error rate achieved. The best results occur when both the iconic and linguistic models mutually correct one another. We have observed recognition error rates driven down by nearly an order of magnitude fully automatically without supervision (or indeed without any user intervention or interaction). Improvement is nearly monotonic, and

  4. Visual Recognition Memory across Contexts

    ERIC Educational Resources Information Center

    Jones, Emily J. H.; Pascalis, Olivier; Eacott, Madeline J.; Herbert, Jane S.

    2011-01-01

    In two experiments, we investigated the development of representational flexibility in visual recognition memory during infancy using the Visual Paired Comparison (VPC) task. In Experiment 1, 6- and 9-month-old infants exhibited recognition when familiarization and test occurred in the same room, but showed no evidence of recognition when…

  5. Word Recognition in Auditory Cortex

    ERIC Educational Resources Information Center

    DeWitt, Iain D. J.

    2013-01-01

    Although spoken word recognition is more fundamental to human communication than text recognition, knowledge of word-processing in auditory cortex is comparatively impoverished. This dissertation synthesizes current models of auditory cortex, models of cortical pattern recognition, models of single-word reading, results in phonetics and results in…

  6. Audio-visual gender recognition

    NASA Astrophysics Data System (ADS)

    Liu, Ming; Xu, Xun; Huang, Thomas S.

    2007-11-01

    Combining different modalities for pattern recognition task is a very promising field. Basically, human always fuse information from different modalities to recognize object and perform inference, etc. Audio-Visual gender recognition is one of the most common task in human social communication. Human can identify the gender by facial appearance, by speech and also by body gait. Indeed, human gender recognition is a multi-modal data acquisition and processing procedure. However, computational multimodal gender recognition has not been extensively investigated in the literature. In this paper, speech and facial image are fused to perform a mutli-modal gender recognition for exploring the improvement of combining different modalities.

  7. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2013 CFR

    2013-01-01

    ... 8 Aliens and Nationality 1 2013-01-01 2013-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2... IMMIGRATION REGULATIONS REPRESENTATION AND APPEARANCES § 1292.2 Organizations qualified for...

  8. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 8 Aliens and Nationality 1 2014-01-01 2014-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2... IMMIGRATION REGULATIONS REPRESENTATION AND APPEARANCES § 1292.2 Organizations qualified for...

  9. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2012 CFR

    2012-01-01

    ... 8 Aliens and Nationality 1 2012-01-01 2012-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2... IMMIGRATION REGULATIONS REPRESENTATION AND APPEARANCES § 1292.2 Organizations qualified for...

  10. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 8 Aliens and Nationality 1 2011-01-01 2011-01-01 false Organizations qualified for recognition; requests for recognition; withdrawal of recognition; accreditation of representatives; roster. 1292.2... IMMIGRATION REGULATIONS REPRESENTATION AND APPEARANCES § 1292.2 Organizations qualified for...

  11. Recognition of Teaching Excellence*

    PubMed Central

    Piascik, Peggy; Medina, Melissa; Pittenger, Amy; Rose, Renee; Creekmore, Freddy; Soltis, Robert; Bouldin, Alicia; Schwarz, Lindsay; Scott, Steven

    2010-01-01

    The 2008-2009 Task Force for the Recognition of Teaching Excellence was charged by the AACP Council of Faculties Leadership to examine teaching excellence by collecting best practices from colleges and schools of pharmacy, evaluating the literature to identify evidence-based criteria for excellent teaching, and recommending appropriate means to acknowledge and reward teaching excellence. This report defines teaching excellence and discusses a variety of ways to assess it, including student, alumni, peer, and self-assessment. The task force identifies important considerations that colleges and schools must address when establishing teaching recognition programs including the purpose, criteria, number and mix of awards, frequency, type of award, and method of nominating and determining awardees. The report concludes with recommendations for the academy to consider when establishing and revising teaching award programs. PMID:21301598

  12. Halogen bonding anion recognition.

    PubMed

    Brown, Asha; Beer, Paul D

    2016-07-01

    A halogen bond is an attractive non-covalent interaction between an electrophilic region in a covalently bonded halogen atom and a Lewis base. While these interactions have long been exploited as a tool in crystal engineering their powerful ability to direct supramolecular self-assembly and molecular recognition processes in solution has, until recently, been overlooked. During the last decade however an ever-increasing number of studies on solution-phase halogen-bond-mediated anion recognition processes has emerged. This Feature Article summarises advancements which have been made thus far in this rapidly developing research area. We survey the use of iodoperfluoroarene, haloimidazolium and halotriazole/triazolium halogen-bond-donor motifs in anion receptor design, before providing an account of our research into the application of mechanically interlocked rotaxane and catenane frameworks as halogen bonding anion host systems. PMID:27273600

  13. Pattern Recognition by Pentraxins

    PubMed Central

    Agrawal, Alok; Singh, Prem Prakash; Bottazzi, Barbara; Garlanda, Cecilia; Mantovani, Alberto

    2012-01-01

    Pentraxins are a family of evolutionarily conserved pattern-recognition proteins that are made up of five identical subunits. Based on the primary structure of the subunit, the pentraxins are divided into two groups: short pentraxins and long pentraxins. C-reactive protein (CRP) and serum amyloid P-component (SAP) are the two short pentraxins. The prototype protein of the long pentraxin group is pentraxin 3 (PTX3). CRP and SAP are produced primarily in the liver while PTX3 is produced in a variety of tissues during inflammation. The main functions of short pentraxins are to recognize a variety of pathogenic agents and then to either eliminate them or neutralize their harmful effects by utilizing the complement pathways and macrophages in the host. CRP binds to modified low-density lipoproteins, bacterial polysaccharides, apoptotic cells, and nuclear materials. By virtue of these recognition functions, CRP participates in the resolution of cardiovascular, infectious, and autoimmune diseases. SAP recognizes carbohydrates, nuclear substances, and amyloid fibrils and thus participates in the resolution of infectious diseases, autoimmunity, and amyloidosis. PTX3 interacts with several ligands, including growth factors, extracellular matrix component and selected pathogens, playing a role in complement activation and facilitating pathogen recognition by phagocytes. In addition, data in gene-targeted mice show that PTX3 is essential in female fertility, participating in the assembly of the cumulus oophorus extra-cellular matrix. PTX3 is therefore a nonredundant component of the humoral arm of innate immunity as well as a tuner of inflammation. Thus, in conjunction with the other components of innate immunity, the pentraxins use their pattern-recognition property for the benefit of the host. PMID:19799114

  14. Video Scene Recognition System

    NASA Astrophysics Data System (ADS)

    Wong, Robert Y.; Sallak, Rashid M.

    1983-03-01

    Microprocessors are used to show a possible implementation of a multiprocessoi system for video scene recognition operations. The system was designed in the multiple input stream and multiple data stream (MIMD) configuration. "Autonomous cooperation" among the working processors is supervised by a global operating system, the heart of which is the scheduler. The design of the scheduler and the overall operations of the system are discussed.

  15. Metamorphopsia and letter recognition

    PubMed Central

    Wiecek, Emily; Dakin, Steven C.; Bex, Peter

    2014-01-01

    Acuity is the most commonly used measure of visual function, and reductions in acuity are associated with most eye diseases. Metamorphopsia—a perceived distortion of visual space—is another common symptom of visual impairment and is currently assessed qualitatively using Amsler (1953) charts. In order to quantify the impact of metamorphopsia on acuity, we measured the effect of physical spatial distortion on letter recognition. Following earlier work showing that letter recognition is tuned to specific spatial frequency (SF) channels, we hypothesized that the effect of distortion might depend on the spatial scale of visual distortion just as it depends on the spatial scale of masking noise. Six normally sighted observers completed a 26 alternate forced choice (AFC) Sloan letter identification task at five different viewing distances, and the letters underwent different levels of spatial distortion. Distortion was controlled using spatially band-pass filtered noise that spatially remapped pixel locations. Noise was varied over five spatial frequencies and five magnitudes. Performance was modeled with logistic regression and worsened linearly with increasing distortion magnitude and decreasing letter size. We found that retinal SF affects distortion at midrange frequencies and can be explained with the tuning of a basic contrast sensitivity function, while object-centered distortion SF follows a similar pattern of letter object recognition sensitivity and is tuned to approximately three cycles per letter (CPL). The interaction between letter size and distortion makes acuity an unreliable outcome for metamorphopsia assessment. PMID:25453116

  16. Autonomous underwater barcode recognition

    NASA Astrophysics Data System (ADS)

    Schulze, Karl R.

    2003-11-01

    Wide area symbol recognition is a task that plagues many autonomous vehicles. A process is needed first to recognize if the symbol is present, and if so where it is. Once the symbol's position is detected it must be analyzed and recognized. In this scenario we have a submersible attempting to locate man made objects on the bottom of a large water basin. These man made objects have bar codes on them that need to be read and the position of the code needs to be recorded relative to where it is in the entire pond. A two step process has been developed to allow the position recognition within a frame to be dealt with on a separate DSP associated with one of three total cameras. The object recognition is then dealt with on a high speed computer aboard the vehicle to read the proper code. The reading is done using a statistics based approach that assumes a noisy, but contrasting background. This approach has proven to be effective in environments in which the background has very little ordered noise, such as the bottom of lakes and ponds, but requires very high clarity in order to capture a suitable image.

  17. Techniques for automatic speech recognition

    NASA Astrophysics Data System (ADS)

    Moore, R. K.

    1983-05-01

    A brief insight into some of the algorithms that lie behind current automatic speech recognition system is provided. Early phonetically based approaches were not particularly successful, due mainly to a lack of appreciation of the problems involved. These problems are summarized, and various recognition techniques are reviewed in the contect of the solutions that they provide. It is pointed out that the majority of currently available speech recognition equipments employ a "whole-word' pattern matching approach which, although relatively simple, has proved particularly successful in its ability to recognize speech. The concepts of time-normalizing plays a central role in this type of recognition process and a family of such algorithms is described in detail. The technique of dynamic time warping is not only capable of providing good performance for isolated word recognition, but how it is also extended to the recognition of connected speech (thereby removing one of the most severe limitations of early speech recognition equipment).

  18. Substrate recognition of N,N'-diacetylchitobiose deacetylase from Pyrococcus horikoshii.

    PubMed

    Nakamura, Tsutomu; Yonezawa, Yasushige; Tsuchiya, Yuko; Niiyama, Mayumi; Ida, Kurumi; Oshima, Maki; Morita, Junji; Uegaki, Koichi

    2016-09-01

    Enzymes of carbohydrate esterase (CE) family 14 catalyze hydrolysis of N-acetyl groups at the non-reducing end of the N-acetylglucosamine (GlcNAc) residue of chitooligosaccharides or related compounds. N,N'-diacetylchitobiose deacetylase (Dac) belongs to the CE-14 family and plays a role in the chitinolytic pathway in archaea by deacetylating N,N'-diacetylchitobiose (GlcNAc2), which is the end product of chitinase. In this study, we revealed the structural basis of reaction specificity in CE-14 deacetylases by solving a crystal structure of Dac from Pyrococcus horikoshii (Ph-Dac) in complex with a novel reaction intermediate analog. We developed 2-deoxy-2-methylphosphoramido-d-glucose (MPG) as the analog of the tetrahedral oxyanion intermediate of the monosaccharide substrate GlcNAc. The crystal structure of Ph-Dac in complex with MPG demonstrated that Arg92, Asp115, and His152 side chains interact with hydroxyl groups of the glucose moiety of the non-reducing-end GlcNAc residue. The amino acid residues responsible for recognition of the MPG glucose moiety are spatially conserved in other CE-14 deacetylases. Molecular dynamics simulation of the structure of the Ph-Dac-GlcNAc2 complex indicated that the reducing GlcNAc residue is placed in a large intermolecular cleft and is not involved with specific interactions with the enzyme. This observation was consistent with results indicating that Ph-Dac displayed similar kinetic parameters for both GlcNAc and GlcNAc2. This study provides the structural basis of reaction-site specificity of Dac and related CE-14 enzymes. PMID:27456364

  19. A fibrinogen-related protein identified from hepatopancreas of crayfish is a potential pattern recognition receptor.

    PubMed

    Chen, Qiming; Bai, Suhua; Dong, Chaohua

    2016-09-01

    Fibrinogen-related protein (FREP) family is a large group of proteins containing fibrinogen-like (FBG) domain and plays multiple physiological roles in animals. However, their immune functions in crayfish are not fully explored. In the present study, a novel fibrinogen-like protein (designated as PcFBN1) was identified and characterized from hepatopancreas of red swamp crayfish Procambarus clarkii. The cDNA sequence of PcFBN1 contains an open reading frame (ORF) of 1353 bp encoding a protein of 450 amino acids. Sequence and structural analysis indicated that PcFBN1 contains an FBG domain in C-terminal and a putative signal peptide of 19 amino acids in N-terminal. Semi-quantitative PCR revealed that the main expression of PcFBN1 was observed in hepatopancreas and hemocyte. Temporal expression analysis exhibited that PcFBN1 expression could be significantly induced by heat-killed Aeromonas hydrophila. Tissue distribution and temporal change of PcFBN1 suggested that PcFBN1 may be involved in immune responses of red swamp crayfish. Recombinant PcFBN1 protein binds and agglutinates both gram-negative bacteria Escherichia coli and gram-positive bacteria Micrococcus lysodeikticus. Moreover, binding and agglutination is Ca(2+) dependent. Further analysis indicated that PcFBN1 recognizes some acetyl group-containing substance LPS and PGN. RNAi experiment revealed that PcFBN1 is required for bacterial clearance and survival from A. hydrophila infection. Reduction of PcFBN1 expression significantly decreased the survival and enhanced the number of A. hydrophila in the hemolymph. These results indicated that PcFBN1 plays an important role in the innate immunity of red swamp crayfish as a potential pattern recognition receptor. PMID:27417229

  20. Automatic speaker recognition system

    NASA Astrophysics Data System (ADS)

    Higgins, Alan; Naylor, Joe

    1984-07-01

    The Defense Communications Division of ITT (ITTDCD) has developed an automatic speaker recognition (ASR) system that meets the functional requirements defined in NRL's Statement of Work. This report is organized as follows. Chapter 2 is a short history of the development of the ASR system, both the algorithm and the implementation. Chapter 3 describes the methodology of system testing, and Chapter 4 summarizes test results. In Chapter 5, some additional testing performed using GFM test material is discussed. Conclusions derived from the contract work are given in Chapter 6.

  1. Genetic specificity of face recognition

    PubMed Central

    Shakeshaft, Nicholas G.; Plomin, Robert

    2015-01-01

    Specific cognitive abilities in diverse domains are typically found to be highly heritable and substantially correlated with general cognitive ability (g), both phenotypically and genetically. Recent twin studies have found the ability to memorize and recognize faces to be an exception, being similarly heritable but phenotypically substantially uncorrelated both with g and with general object recognition. However, the genetic relationships between face recognition and other abilities (the extent to which they share a common genetic etiology) cannot be determined from phenotypic associations. In this, to our knowledge, first study of the genetic associations between face recognition and other domains, 2,000 18- and 19-year-old United Kingdom twins completed tests assessing their face recognition, object recognition, and general cognitive abilities. Results confirmed the substantial heritability of face recognition (61%), and multivariate genetic analyses found that most of this genetic influence is unique and not shared with other cognitive abilities. PMID:26417086

  2. Sudden event recognition: a survey.

    PubMed

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

  3. Sudden Event Recognition: A Survey

    PubMed Central

    Suriani, Nor Surayahani; Hussain, Aini; Zulkifley, Mohd Asyraf

    2013-01-01

    Event recognition is one of the most active research areas in video surveillance fields. Advancement in event recognition systems mainly aims to provide convenience, safety and an efficient lifestyle for humanity. A precise, accurate and robust approach is necessary to enable event recognition systems to respond to sudden changes in various uncontrolled environments, such as the case of an emergency, physical threat and a fire or bomb alert. The performance of sudden event recognition systems depends heavily on the accuracy of low level processing, like detection, recognition, tracking and machine learning algorithms. This survey aims to detect and characterize a sudden event, which is a subset of an abnormal event in several video surveillance applications. This paper discusses the following in detail: (1) the importance of a sudden event over a general anomalous event; (2) frameworks used in sudden event recognition; (3) the requirements and comparative studies of a sudden event recognition system and (4) various decision-making approaches for sudden event recognition. The advantages and drawbacks of using 3D images from multiple cameras for real-time application are also discussed. The paper concludes with suggestions for future research directions in sudden event recognition. PMID:23921828

  4. Complex Event Recognition Architecture

    NASA Technical Reports Server (NTRS)

    Fitzgerald, William A.; Firby, R. James

    2009-01-01

    Complex Event Recognition Architecture (CERA) is the name of a computational architecture, and software that implements the architecture, for recognizing complex event patterns that may be spread across multiple streams of input data. One of the main components of CERA is an intuitive event pattern language that simplifies what would otherwise be the complex, difficult tasks of creating logical descriptions of combinations of temporal events and defining rules for combining information from different sources over time. In this language, recognition patterns are defined in simple, declarative statements that combine point events from given input streams with those from other streams, using conjunction, disjunction, and negation. Patterns can be built on one another recursively to describe very rich, temporally extended combinations of events. Thereafter, a run-time matching algorithm in CERA efficiently matches these patterns against input data and signals when patterns are recognized. CERA can be used to monitor complex systems and to signal operators or initiate corrective actions when anomalous conditions are recognized. CERA can be run as a stand-alone monitoring system, or it can be integrated into a larger system to automatically trigger responses to changing environments or problematic situations.

  5. Retina vascular network recognition

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Passerini, Giorgio; Puliti, Paolo; Zingaretti, Primo

    1993-09-01

    The analysis of morphological and structural modifications of the retina vascular network is an interesting investigation method in the study of diabetes and hypertension. Normally this analysis is carried out by qualitative evaluations, according to standardized criteria, though medical research attaches great importance to quantitative analysis of vessel color, shape and dimensions. The paper describes a system which automatically segments and recognizes the ocular fundus circulation and micro circulation network, and extracts a set of features related to morphometric aspects of vessels. For this class of images the classical segmentation methods seem weak. We propose a computer vision system in which segmentation and recognition phases are strictly connected. The system is hierarchically organized in four modules. Firstly the Image Enhancement Module (IEM) operates a set of custom image enhancements to remove blur and to prepare data for subsequent segmentation and recognition processes. Secondly the Papilla Border Analysis Module (PBAM) automatically recognizes number, position and local diameter of blood vessels departing from optical papilla. Then the Vessel Tracking Module (VTM) analyses vessels comparing the results of body and edge tracking and detects branches and crossings. Finally the Feature Extraction Module evaluates PBAM and VTM output data and extracts some numerical indexes. Used algorithms appear to be robust and have been successfully tested on various ocular fundus images.

  6. Naval ship recognition

    NASA Astrophysics Data System (ADS)

    Camino García, I.; Zölzer, U.

    2012-09-01

    Object recognition is a very interesting task with multiple applications and for that reason it has been dealt with very intensively in the last years. In particular, the application to naval ship pictures may facilitate the work of the coastguards or the navy. However, this type of images entails some difficulties due to their specific environment. Water reflects the light and as a consequence, some areas may presumably show different brightness and color. Waves from wind or moving ships pose a problem due to the additional edges that they produce. The camouflage of ships in the military context is also an issue to take into account. Therefore, it is difficult to propose a simple method that is valid for every image. A discussion about which techniques may solve these problems is presented and finally a combined solution based on contour recognition is suggested. Test images are preprocessed by histogram stretching. Then, the Canny method is applied to the image and to the reference contour in order to obtain not only their edges, but also their respective orientations. The problem of recognizing the reference contour within the detected edges is addressed by making use of the Generalized Hough Transform (GHT).

  7. The Legal Recognition of Sign Languages

    ERIC Educational Resources Information Center

    De Meulder, Maartje

    2015-01-01

    This article provides an analytical overview of the different types of explicit legal recognition of sign languages. Five categories are distinguished: constitutional recognition, recognition by means of general language legislation, recognition by means of a sign language law or act, recognition by means of a sign language law or act including…

  8. Teaching and the Dialectic of Recognition

    ERIC Educational Resources Information Center

    Huttunen, Rauno; Heikkinen, Hannu L. T.

    2004-01-01

    In this article, the processes of recognition within education are discussed. Frequently, recognition is reduced to polite behaviour or etiquette. Another narrow view of recognition is, behaviouristically speaking, to regard it as mere feedback. We claim that authentic recognition is a different matter. Receiving recognition, as Charles Taylor has…

  9. Chemical recognition software

    SciTech Connect

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.J. Jr.; Tisone, G.C.

    1994-12-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures. even when the mixture is noisy and contaminated with unknowns.

  10. Chemical recognition software

    SciTech Connect

    Wagner, J.S.; Trahan, M.W.; Nelson, W.E.; Hargis, P.H. Jr.; Tisone, G.C.

    1994-06-01

    We have developed a capability to make real time concentration measurements of individual chemicals in a complex mixture using a multispectral laser remote sensing system. Our chemical recognition and analysis software consists of three parts: (1) a rigorous multivariate analysis package for quantitative concentration and uncertainty estimates, (2) a genetic optimizer which customizes and tailors the multivariate algorithm for a particular application, and (3) an intelligent neural net chemical filter which pre-selects from the chemical database to find the appropriate candidate chemicals for quantitative analyses by the multivariate algorithms, as well as providing a quick-look concentration estimate and consistency check. Detailed simulations using both laboratory fluorescence data and computer synthesized spectra indicate that our software can make accurate concentration estimates from complex multicomponent mixtures, even when the mixture is noisy and contaminated with unknowns.

  11. Early recognition of speech

    PubMed Central

    Remez, Robert E; Thomas, Emily F

    2013-01-01

    Classic research on the perception of speech sought to identify minimal acoustic correlates of each consonant and vowel. In explaining perception, this view designated momentary components of an acoustic spectrum as cues to the recognition of elementary phonemes. This conceptualization of speech perception is untenable given the findings of phonetic sensitivity to modulation independent of the acoustic and auditory form of the carrier. The empirical key is provided by studies of the perceptual organization of speech, a low-level integrative function that finds and follows the sensory effects of speech amid concurrent events. These projects have shown that the perceptual organization of speech is keyed to modulation; fast; unlearned; nonsymbolic; indifferent to short-term auditory properties; and organization requires attention. The ineluctably multisensory nature of speech perception also imposes conditions that distinguish language among cognitive systems. WIREs Cogn Sci 2013, 4:213–223. doi: 10.1002/wcs.1213 PMID:23926454

  12. Recognition Using Hybrid Classifiers.

    PubMed

    Osadchy, Margarita; Keren, Daniel; Raviv, Dolev

    2016-04-01

    A canonical problem in computer vision is category recognition (e.g., find all instances of human faces, cars etc., in an image). Typically, the input for training a binary classifier is a relatively small sample of positive examples, and a huge sample of negative examples, which can be very diverse, consisting of images from a large number of categories. The difficulty of the problem sharply increases with the dimension and size of the negative example set. We propose to alleviate this problem by applying a "hybrid" classifier, which replaces the negative samples by a prior, and then finds a hyperplane which separates the positive samples from this prior. The method is extended to kernel space and to an ensemble-based approach. The resulting binary classifiers achieve an identical or better classification rate than SVM, while requiring far smaller memory and lower computational complexity to train and apply. PMID:26959677

  13. Automatic speech recognition

    NASA Astrophysics Data System (ADS)

    Espy-Wilson, Carol

    2005-04-01

    Great strides have been made in the development of automatic speech recognition (ASR) technology over the past thirty years. Most of this effort has been centered around the extension and improvement of Hidden Markov Model (HMM) approaches to ASR. Current commercially-available and industry systems based on HMMs can perform well for certain situational tasks that restrict variability such as phone dialing or limited voice commands. However, the holy grail of ASR systems is performance comparable to humans-in other words, the ability to automatically transcribe unrestricted conversational speech spoken by an infinite number of speakers under varying acoustic environments. This goal is far from being reached. Key to the success of ASR is effective modeling of variability in the speech signal. This tutorial will review the basics of ASR and the various ways in which our current knowledge of speech production, speech perception and prosody can be exploited to improve robustness at every level of the system.

  14. Methods of Teaching Speech Recognition

    ERIC Educational Resources Information Center

    Rader, Martha H.; Bailey, Glenn A.

    2010-01-01

    Objective: This article introduces the history and development of speech recognition, addresses its role in the business curriculum, outlines related national and state standards, describes instructional strategies, and discusses the assessment of student achievement in speech recognition classes. Methods: Research methods included a synthesis of…

  15. Computer image processing and recognition

    NASA Technical Reports Server (NTRS)

    Hall, E. L.

    1979-01-01

    A systematic introduction to the concepts and techniques of computer image processing and recognition is presented. Consideration is given to such topics as image formation and perception; computer representation of images; image enhancement and restoration; reconstruction from projections; digital television, encoding, and data compression; scene understanding; scene matching and recognition; and processing techniques for linear systems.

  16. Online handwritten mathematical expression recognition

    NASA Astrophysics Data System (ADS)

    Büyükbayrak, Hakan; Yanikoglu, Berrin; Erçil, Aytül

    2007-01-01

    We describe a system for recognizing online, handwritten mathematical expressions. The system is designed with a user-interface for writing scientific articles, supporting the recognition of basic mathematical expressions as well as integrals, summations, matrices etc. A feed-forward neural network recognizes symbols which are assumed to be single-stroke and a recursive algorithm parses the expression by combining neural network output and the structure of the expression. Preliminary results show that writer-dependent recognition rates are very high (99.8%) while writer-independent symbol recognition rates are lower (75%). The interface associated with the proposed system integrates the built-in recognition capabilities of the Microsoft's Tablet PC API for recognizing textual input and supports conversion of hand-drawn figures into PNG format. This enables the user to enter text, mathematics and draw figures in a single interface. After recognition, all output is combined into one LATEX code and compiled into a PDF file.

  17. A face recognition embedded system

    NASA Astrophysics Data System (ADS)

    Pun, Kwok Ho; Moon, Yiu Sang; Tsang, Chi Chiu; Chow, Chun Tak; Chan, Siu Man

    2005-03-01

    This paper presents an experimental study of the implementation of a face recognition system in embedded systems. To investigate the feasibility and practicality of real time face recognition on such systems, a door access control system based on face recognition is built. Due to the limited computation power of embedded device, a semi-automatic scheme for face detection and eye location is proposed to solve these computationally hard problems. It is found that to achieve real time performance, optimization of the core face recognition module is needed. As a result, extensive profiling is done to pinpoint the execution hotspots in the system and optimization are carried out. After careful precision analysis, all slow floating point calculations are replaced with their fixed-point versions. Experimental results show that real time performance can be achieved without significant loss in recognition accuracy.

  18. Speech Recognition: How Do We Teach It?

    ERIC Educational Resources Information Center

    Barksdale, Karl

    2002-01-01

    States that growing use of speech recognition software has made voice writing an essential computer skill. Describes how to present the topic, develop basic speech recognition skills, and teach speech recognition outlining, writing, proofreading, and editing. (Contains 14 references.) (SK)

  19. Accuracy enhanced thermal face recognition

    NASA Astrophysics Data System (ADS)

    Lin, Chun-Fu; Lin, Sheng-Fuu

    2013-11-01

    Human face recognition has been generally researched for the last three decades. Face recognition with thermal image has begun to attract significant attention gradually since illumination of environment would not affect the recognition performance. However, the recognition performance of traditional thermal face recognizer is still insufficient in practical application. This study presents a novel thermal face recognizer employing not only thermal features but also critical facial geometric features which would not be influenced by hair style to improve the recognition performance. A three-layer back-propagation feed-forward neural network is applied as the classifier. Traditional thermal face recognizers only use the indirect information of the topography of blood vessels like thermogram as features. To overcome this limitation, the proposed thermal face recognizer can use not only the indirect information but also the direct information of the topography of blood vessels which is unique for every human. Moreover, the recognition performance of the proposed thermal features would not decrease even if the hair of frontal bone varies, the eye blinks or the nose breathes. Experimental results show that the proposed features are significantly more effective than traditional thermal features and the recognition performance of thermal face recognizer is improved.

  20. Macromolecular recognition: Recognition of polymer side chains by cyclodextrin

    NASA Astrophysics Data System (ADS)

    Hashidzume, Akihito; Harada, Akira

    2015-12-01

    The interaction of cyclodextrins (CD) with water soluble polymers possessing guest residues has been investigated as model systems in biological molecular recognition. The selectivity of interaction of CD with polymer-carrying guest residues is controlled by polymer chains, i.e., the steric effect of polymer main chain, the conformational effect of polymer main chain, and multi-site interaction. Macroscopic assemblies have been also realized based on molecular recognition using polyacrylamide-based gels possessing CD and guest residues.

  1. Arabic character recognition

    NASA Astrophysics Data System (ADS)

    Allam, May

    1994-03-01

    This paper presents a complete system for learning and recognizing Arabic characters. Arabic OCR faces technical problems not encountered in other languages such as cursiveness, overriding and overlapping of characters, multiple shapes per character and the presence of vowels above and below the characters. The proposed approach relies on the fact that the process of connecting Arabic characters to produce cursive writing tends to form a fictitious baseline. During preprocessing, contour analysis provides both component isolation and baseline location. In the feature extraction phase, the words are processed from right to left to generate a sequence of labels. Each label is one of a predetermined codebook that represents all possible bit distribution with respect to the baseline. At a certain position, which depends on the label context, a segmentation decision is taken. During training, a model is generated for each character. This model describes the probability of the occurrence of the labels at each vertical position. During recognition, the probability of the label observation sequence is computed and accumulated. The system has been tested on different typewritten, typeset fonts and diacriticized versions of both and the evaluation results are presented.

  2. Measure recognition problem.

    PubMed

    Dzamonja, Mirna

    2006-12-15

    This is a paper in mathematics, specifically in set theory. On the example of the measure recognition problem (MRP), the paper highlights the phenomenon of the utility of a multidisciplinary mathematical approach to a single mathematical problem, in particular, the value of a set-theoretic analysis. MRP asks if for a given Boolean algebra, B, and a property, Phi, of measures, one can recognize by purely combinatorial means if B supports a strictly positive measure with property Phi. The most famous instance of this problem is MRP (countable additivity), and in the first part of the paper, we survey the known results on this and some other problems. We show how these results naturally lead to asking about two other specific instances of the problem MRP, namely MRP (non-atomic) and MRP (separable). Then, we show how our recent work gives an easy solution to the former of these problems and some partial information about the latter. The long-term goal of this line of research is to obtain a structure theory of Boolean algebras that support a finitely additive strictly positive measure, along the lines of Maharam theorem, which gives such a structure theorem for measure algebras. PMID:17090453

  3. Human recognition at a distance

    NASA Astrophysics Data System (ADS)

    Bhanu, Bir

    2007-11-01

    Recognizing people at a distance is challenging from various considerations, including sensing, robust processing algorithms, changing environmental conditions and fusing multiple modalities. This paper considers face, side face, gait and ear and their possible fusion for human recognition. It presents an overview of some of the techniques that we have developed for (a) super-resolution-based face recognition in video, (b) gait-based recognition in video, (c) fusion of super-resolved side face and gait in video, (d) ear recognition in color/range images, and (e) fusion performance prediction and validation. It presents various real-world examples to illustrate the ideas and points out the relative merits of the approaches that are discussed.

  4. The neuroecology of competitor recognition.

    PubMed

    Grether, Gregory F

    2011-11-01

    Territorial animals can be expected to distinguish among the types of competitors and noncompetitors that they encounter on a regular basis, including prospective mates and rivals of their own species, but they may not correctly classify individuals of other species. Closely related species often have similar phenotypes and this can cause confusion when formerly allopatric populations first come into contact. Errors in recognizing competitors can have important ecological and evolutionary effects. I review what is known about the mechanisms of competitor recognition in animals generally, focusing on cases in which the targets of recognition include other species. Case studies include damselflies, ants, skinks, salamanders, reef fishes, and birds. In general, recognition systems consist of a phenotypic cue (e.g., chemical, color, song), a neural template against which cues are compared, a motor response (e.g., aggression), and sensory integration circuits for context dependency of the response (if any). Little is known about how competitor recognition systems work at the neural level, but inferences about specificity of cues and about sensory integration can be drawn from the responses of territory residents to simulated intruders. Competitor recognition often involves multiple cues in the same, or different, sensory modalities. The same cues and templates are often, but not always, used for intraspecific and interspecific recognition. Experiments have shown that imprinting on local cues is common, which may enable templates to track evolved changes in cues automatically. The dependence of aggression and tolerance on context is important even in the simplest systems. Species in which mechanisms of competitor recognition are best known offer untapped opportunities to examine how competitor-recognition systems evolve (e.g., by comparing allopatric and sympatric populations). Cues that are gene products (peptides, proteins) may provide insights into rates of evolution

  5. On Tangut Historical Documents Recognition*

    NASA Astrophysics Data System (ADS)

    Liu, Changqing

    As the Tangut studies have made progress, a considerable number of Tangut historical documents' copies have been published. It is of great importance to carry out digitalization and domestication of these copies. The paper firstly makes an initial processing of images by global threshold, then dissect the photocopies by scanning. Finally adopts the recognition approach of principal component analysis. The experiment shows that a better recognition can be achieved by calculation without extra time.

  6. Combinatorial approaches to gene recognition.

    PubMed

    Roytberg, M A; Astakhova, T V; Gelfand, M S

    1997-01-01

    Recognition of genes via exon assembly approaches leads naturally to the use of dynamic programming. We consider the general graph-theoretical formulation of the exon assembly problem and analyze in detail some specific variants: multicriterial optimization in the case of non-linear gene-scoring functions; context-dependent schemes for scoring exons and related procedures for exon filtering; and highly specific recognition of arbitrary gene segments, oligonucleotide probes and polymerase chain reaction (PCR) primers. PMID:9440930

  7. Success with voice recognition.

    PubMed

    Sferrella, Sheila M

    2003-01-01

    You need a compelling reason to implement voice recognition technology. At my institution, the compelling reason was a turnaround time for Radiology results of more than two days. Only 41 percent of our reports were transcribed and signed within 24 hours. In November 1998, a team from Lehigh Valley Hospital went to RSNA and reviewed every voice system on the market. The evaluation was done with the radiologist workflow in mind, and we came back from the meeting with the vendor selection completed. The next steps included developing a business plan, approval of funds, reference calls to more than 15 sites and contract negotiation, all of which took about six months. The department of Radiology at Lehigh Valley Hospital and Health Network (LVHHN) is a multi-site center that performs over 360,000 procedures annually. The department handles all modalities of radiology: general diagnosis, neuroradiology, ultrasound, CT Scan, MRI, interventional radiology, arthography, myelography, bone densitometry, nuclear medicine, PET imaging, vascular lab and other advanced procedures. The department consists of 200 FTEs and a medical staff of more than 40 radiologists. The budget is in the $10.3 million range. There are three hospital sites and four outpatient imaging center sites where services are provided. At Lehigh Valley Hospital, radiologists are not dedicated to one subspecialty, so implementing a voice system by modality was not an option. Because transcription was so far behind, we needed to eliminate that part of the process. As a result, we decided to deploy the system all at once and with the radiologists as editors. The planning and testing phase took about four months, and the implementation took two weeks. We deployed over 40 workstations and trained close to 50 physicians. The radiologists brought in an extra radiologist from our group for the two weeks of training. That allowed us to train without taking a radiologist out of the department. We trained three to six

  8. Sampling design for face recognition

    NASA Astrophysics Data System (ADS)

    Yan, Yanjun; Osadciw, Lisa A.

    2006-04-01

    A face recognition system consists of two integrated parts: One is the face recognition algorithm, the other is the selected classifier and derived features by the algorithm from a data set. The face recognition algorithm definitely plays a central role, but this paper does not aim at evaluating the algorithm, but deriving the best features for this algorithm from a specific database through sampling design of the training set, which directs how the sample should be collected and dictates the sample space. Sampling design can help exert the full potential of the face recognition algorithm without overhaul. Conventional statistical analysis usually assume some distribution to draw the inference, but the design-based inference does not assume any distribution of the data and it does not assume the independency between the sample observations. The simulations illustrates that the systematic sampling scheme performs better than the simple random sampling scheme, and the systematic sampling is comparable to using all available training images in recognition performance. Meanwhile the sampling schemes can save the system resources and alleviate the overfitting problem. However, the post stratification by sex is not shown to be significant in improving the recognition performance.

  9. Document Form and Character Recognition using SVM

    NASA Astrophysics Data System (ADS)

    Park, Sang-Sung; Shin, Young-Geun; Jung, Won-Kyo; Ahn, Dong-Kyu; Jang, Dong-Sik

    2009-08-01

    Because of development of computer and information communication, EDI (Electronic Data Interchange) has been developing. There is OCR (Optical Character Recognition) of Pattern recognition technology for EDI. OCR contributed to changing many manual in the past into automation. But for the more perfect database of document, much manual is needed for excluding unnecessary recognition. To resolve this problem, we propose document form based character recognition method in this study. Proposed method is divided into document form recognition part and character recognition part. Especially, in character recognition, change character into binarization by using SVM algorithm and extract more correct feature value.

  10. Evidence for Surface Recognition by a Cholesterol-Recognition Peptide.

    PubMed

    Mukai, Masaru; Glover, Kerney Jebrell; Regen, Steven L

    2016-06-21

    Two cholesterol recognition/interaction amino-acid consensus peptides, N-acetyl-LWYIKC-amide, and N-acetyl-CLWYIK-amide, have been coupled to exchangeable mimics of Chol (cholesterol) and Phos (1,2-dipalmitoyl-sn-glycerol-3-phospho-(1'rac-glycerol)) via disulfide bond formation. Equilibration between Chol and Phos via thiolate-disulfide interchange reactions has revealed that both peptides favor Chol as a nearest-neighbor in liquid-disordered (ld) bilayers to the same extent. In contrast, no Chol- or Phos-recognition could be detected by these peptides in analogous liquid-ordered (lo) bilayers. Fluorescence measurements of the tryptophan moiety have shown that both peptides favor the membrane-water interface. Taken together, these results provide strong evidence that the recognition behavior of the LWYIK motif is, fundamentally, a surface phenomenon but that partial penetration into the bilayer is also necessary. PMID:27283494

  11. Bidirectional Modulation of Recognition Memory

    PubMed Central

    Ho, Jonathan W.; Poeta, Devon L.; Jacobson, Tara K.; Zolnik, Timothy A.; Neske, Garrett T.; Connors, Barry W.

    2015-01-01

    Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects. For example, animals and humans with perirhinal damage are unable to distinguish familiar from novel objects in recognition memory tasks. In the normal brain, perirhinal neurons respond to novelty and familiarity by increasing or decreasing firing rates. Recent work also implicates oscillatory activity in the low-beta and low-gamma frequency bands in sensory detection, perception, and recognition. Using optogenetic methods in a spontaneous object exploration (SOR) task, we altered recognition memory performance in rats. In the SOR task, normal rats preferentially explore novel images over familiar ones. We modulated exploratory behavior in this task by optically stimulating channelrhodopsin-expressing perirhinal neurons at various frequencies while rats looked at novel or familiar 2D images. Stimulation at 30–40 Hz during looking caused rats to treat a familiar image as if it were novel by increasing time looking at the image. Stimulation at 30–40 Hz was not effective in increasing exploration of novel images. Stimulation at 10–15 Hz caused animals to treat a novel image as familiar by decreasing time looking at the image, but did not affect looking times for images that were already familiar. We conclude that optical stimulation of PER at different frequencies can alter visual recognition memory bidirectionally. SIGNIFICANCE STATEMENT Recognition of novelty and familiarity are important for learning, memory, and decision making. Perirhinal cortex (PER) has a well established role in the familiarity-based recognition of individual items and objects, but how novelty and familiarity are encoded and transmitted in the brain is not known. Perirhinal neurons respond to novelty and familiarity by changing firing rates, but recent work suggests that brain oscillations may also be important for recognition. In this study, we showed that

  12. Cognitive object recognition system (CORS)

    NASA Astrophysics Data System (ADS)

    Raju, Chaitanya; Varadarajan, Karthik Mahesh; Krishnamurthi, Niyant; Xu, Shuli; Biederman, Irving; Kelley, Troy

    2010-04-01

    We have developed a framework, Cognitive Object Recognition System (CORS), inspired by current neurocomputational models and psychophysical research in which multiple recognition algorithms (shape based geometric primitives, 'geons,' and non-geometric feature-based algorithms) are integrated to provide a comprehensive solution to object recognition and landmarking. Objects are defined as a combination of geons, corresponding to their simple parts, and the relations among the parts. However, those objects that are not easily decomposable into geons, such as bushes and trees, are recognized by CORS using "feature-based" algorithms. The unique interaction between these algorithms is a novel approach that combines the effectiveness of both algorithms and takes us closer to a generalized approach to object recognition. CORS allows recognition of objects through a larger range of poses using geometric primitives and performs well under heavy occlusion - about 35% of object surface is sufficient. Furthermore, geon composition of an object allows image understanding and reasoning even with novel objects. With reliable landmarking capability, the system improves vision-based robot navigation in GPS-denied environments. Feasibility of the CORS system was demonstrated with real stereo images captured from a Pioneer robot. The system can currently identify doors, door handles, staircases, trashcans and other relevant landmarks in the indoor environment.

  13. Optical recognition of biological agents

    NASA Astrophysics Data System (ADS)

    Baumgart, Chris W.; Linder, Kim Dalton; Trujillo, Josh J.

    2008-04-01

    Differentiation between particulate biological agents and non-biological agents is typically performed via a time-consuming "wet chemistry" process or through the use of fluorescent and spectroscopic analysis. However, while these methods can provide definitive recognition of biological agents, many of them have to be performed in a laboratory environment, or are difficult to implement in the field. Optical recognition techniques offer an additional recognition approach that can provide rapid analysis of a material in-situ to identify those materials that may be biological in nature. One possible application is to use these techniques to "screen" suspicious materials and to identify those that are potentially biological in nature. Suspicious materials identified by this screening process can then be analyzed in greater detail using the other, more definitive (but time consuming) analysis techniques. This presentation will describe the results of a feasibility study to determine whether optical pattern recognition techniques can be used to differentiate biological related materials from non-biological materials. As part of this study, feature extraction algorithms were developed utilizing multiple contrast and texture based features to characterize the macroscopic properties of different materials. In addition, several pattern recognition approaches using these features were tested including cluster analysis and neural networks. Test materials included biological agent simulants, biological agent related materials, and non-biological materials (suspicious white powders). Results of a series of feasibility tests will be presented along with a discussion of the potential field applications for these techniques.

  14. Kazakh Traditional Dance Gesture Recognition

    NASA Astrophysics Data System (ADS)

    Nussipbekov, A. K.; Amirgaliyev, E. N.; Hahn, Minsoo

    2014-04-01

    Full body gesture recognition is an important and interdisciplinary research field which is widely used in many application spheres including dance gesture recognition. The rapid growth of technology in recent years brought a lot of contribution in this domain. However it is still challenging task. In this paper we implement Kazakh traditional dance gesture recognition. We use Microsoft Kinect camera to obtain human skeleton and depth information. Then we apply tree-structured Bayesian network and Expectation Maximization algorithm with K-means clustering to calculate conditional linear Gaussians for classifying poses. And finally we use Hidden Markov Model to detect dance gestures. Our main contribution is that we extend Kinect skeleton by adding headwear as a new skeleton joint which is calculated from depth image. This novelty allows us to significantly improve the accuracy of head gesture recognition of a dancer which in turn plays considerable role in whole body gesture recognition. Experimental results show the efficiency of the proposed method and that its performance is comparable to the state-of-the-art system performances.

  15. Sparse representation for vehicle recognition

    NASA Astrophysics Data System (ADS)

    Monnig, Nathan D.; Sakla, Wesam

    2014-06-01

    The Sparse Representation for Classification (SRC) algorithm has been demonstrated to be a state-of-the-art algorithm for facial recognition applications. Wright et al. demonstrate that under certain conditions, the SRC algorithm classification performance is agnostic to choice of linear feature space and highly resilient to image corruption. In this work, we examined the SRC algorithm performance on the vehicle recognition application, using images from the semi-synthetic vehicle database generated by the Air Force Research Laboratory. To represent modern operating conditions, vehicle images were corrupted with noise, blurring, and occlusion, with representation of varying pose and lighting conditions. Experiments suggest that linear feature space selection is important, particularly in the cases involving corrupted images. Overall, the SRC algorithm consistently outperforms a standard k nearest neighbor classifier on the vehicle recognition task.

  16. Mandarin recognition over the telephone

    NASA Astrophysics Data System (ADS)

    Kao, Yuhung

    1996-06-01

    Mandarin Chinese is the official language in China and Taiwan, it is the native language of a quarter of the world population. As the services enabled by speech recognition technology (e.g. telephone voice dialing, information query) become more popular in English, we would like to extend this capability to other languages. Mandarin is one of the major languages under research in our laboratory. This paper describes how we extend our work in English speech recognition into Mandarin. We will described the corpus: Voice Across Taiwan, the training of a complete set of Mandarin syllable models, preliminary performance results and error analysis. A fast prototyping system was built, where a user can write any context free grammar with no restriction of vocabulary, then the grammar can be compiled into recognition models. It enables user to quickly test the performance of a new vocabulary.

  17. Palmprint Recognition across Different Devices

    PubMed Central

    Jia, Wei; Hu, Rong-Xiang; Gui, Jie; Zhao, Yang; Ren, Xiao-Ming

    2012-01-01

    In this paper, the problem of Palmprint Recognition Across Different Devices (PRADD) is investigated, which has not been well studied so far. Since there is no publicly available PRADD image database, we created a non-contact PRADD image database containing 12,000 grayscale captured from 100 subjects using three devices, i.e., one digital camera and two smart-phones. Due to the non-contact image acquisition used, rotation and scale changes between different images captured from a same palm are inevitable. We propose a robust method to calculate the palm width, which can be effectively used for scale normalization of palmprints. On this PRADD image database, we evaluate the recognition performance of three different methods, i.e., subspace learning method, correlation method, and orientation coding based method, respectively. Experiments results show that orientation coding based methods achieved promising recognition performance for PRADD. PMID:22969380

  18. Familiar Person Recognition: Is Autonoetic Consciousness More Likely to Accompany Face Recognition Than Voice Recognition?

    NASA Astrophysics Data System (ADS)

    Barsics, Catherine; Brédart, Serge

    2010-11-01

    Autonoetic consciousness is a fundamental property of human memory, enabling us to experience mental time travel, to recollect past events with a feeling of self-involvement, and to project ourselves in the future. Autonoetic consciousness is a characteristic of episodic memory. By contrast, awareness of the past associated with a mere feeling of familiarity or knowing relies on noetic consciousness, depending on semantic memory integrity. Present research was aimed at evaluating whether conscious recollection of episodic memories is more likely to occur following the recognition of a familiar face than following the recognition of a familiar voice. Recall of semantic information (biographical information) was also assessed. Previous studies that investigated the recall of biographical information following person recognition used faces and voices of famous people as stimuli. In this study, the participants were presented with personally familiar people's voices and faces, thus avoiding the presence of identity cues in the spoken extracts and allowing a stricter control of frequency exposure with both types of stimuli (voices and faces). In the present study, the rate of retrieved episodic memories, associated with autonoetic awareness, was significantly higher from familiar faces than familiar voices even though the level of overall recognition was similar for both these stimuli domains. The same pattern was observed regarding semantic information retrieval. These results and their implications for current Interactive Activation and Competition person recognition models are discussed.

  19. Emotion recognition during cocaine intoxication.

    PubMed

    Kuypers, K P C; Steenbergen, L; Theunissen, E L; Toennes, S W; Ramaekers, J G

    2015-11-01

    Chronic or repeated cocaine use has been linked to impairments in social skills. It is not clear whether cocaine is responsible for this impairment or whether other factors, like polydrug use, distort the observed relation. We aimed to investigate this relation by means of a placebo-controlled experimental study. Additionally, associations between stressor-related activity (cortisol, cardiovascular parameters) induced by the biological stressor cocaine, and potential cocaine effects on emotion recognition were studied. Twenty-four healthy recreational cocaine users participated in this placebo-controlled within-subject study. Participants were tested between 1 and 2 h after treatment with oral cocaine (300 mg) or placebo. Emotion recognition of low and high intensity expressions of basic emotions (fear, anger, disgust, sadness, and happiness) was tested. Findings show that cocaine impaired recognition of negative emotions; this was mediated by the intensity of the presented emotions. When high intensity expressions of Anger and Disgust were shown, performance under influence of cocaine 'normalized' to placebo-like levels while it made identification of Sadness more difficult. The normalization of performance was most notable for participants with the largest cortisol responses in the cocaine condition compared to placebo. It was demonstrated that cocaine impairs recognition of negative emotions, depending on the intensity of emotion expression and cortisol response. PMID:26328908

  20. Ear recognition: a complete system

    NASA Astrophysics Data System (ADS)

    Abaza, Ayman; Harrison, Mary Ann F.

    2013-05-01

    Ear Recognition has recently received significant attention in the literature. Even though current ear recognition systems have reached a certain level of maturity, their success is still limited. This paper presents an efficient complete ear-based biometric system that can process five frames/sec; Hence it can be used for surveillance applications. The ear detection is achieved using Haar features arranged in a cascaded Adaboost classifier. The feature extraction is based on dividing the ear image into several blocks from which Local Binary Pattern feature distributions are extracted. These feature distributions are then fused at the feature level to represent the original ear texture in the classification stage. The contribution of this paper is three fold: (i) Applying a new technique for ear feature extraction, and studying various optimization parameters for that technique; (ii) Presenting a practical ear recognition system and a detailed analysis about error propagation in that system; (iii) Studying the occlusion effect of several ear parts. Detailed experiments show that the proposed ear recognition system achieved better performance (94:34%) compared to other shape-based systems as Scale-invariant feature transform (67:92%). The proposed approach can also handle efficiently hair occlusion. Experimental results show that the proposed system can achieve about (78%) rank-1 identification, even in presence of 60% occlusion.

  1. Face recognition for uncontrolled environments

    NASA Astrophysics Data System (ADS)

    Podilchuk, Christine; Hulbert, William; Flachsbart, Ralph; Barinov, Lev

    2010-04-01

    A new face recognition algorithm has been proposed which is robust to variations in pose, expression, illumination and occlusions such as sunglasses. The algorithm is motivated by the Edit Distance used to determine the similarity between strings of one dimensional data such as DNA and text. The key to this approach is how to extend the concept of an Edit Distance on one-dimensional data to two-dimensional image data. The algorithm is based on mapping one image into another and using the characteristics of the mapping to determine a two-dimensional Pictorial-Edit Distance or P-Edit Distance. We show how the properties of the mapping are similar to insertion, deletion and substitution errors defined in an Edit Distance. This algorithm is particularly well suited for face recognition in uncontrolled environments such as stand-off and other surveillance applications. We will describe an entire system designed for face recognition at a distance including face detection, pose estimation, multi-sample fusion of video frames and identification. Here we describe how the algorithm is used for face recognition at a distance, present some initial results and describe future research directions.(

  2. Fuzzy models for pattern recognition

    SciTech Connect

    Bezdek, James C.; Pal, Sankar K.

    1994-01-01

    FUZZY sets were introduced in 1965 by Lotfi Zadeh as a new way to represent vagueness in everyday life. They are a generalization of conventional set theory, one of the basic structures underlying computational mathematics and models. Computational pattern recognition has played a central role in the development of fuzzy models because fuzzy interpretations of data structures are a very natural and intuitively plausible way to formulate and solve various problems. Fuzzy control theory has also provided a wide variety of real, fielded system applications of fuzzy technology. We shall have little more to say about the growth of fuzzy models in control, except to the extent that pattern recognition algorithms and methods described in this book impact control systems. Collected here are many of the seminal papers in the field. There will be, of course, omissions that are neither by intent nor ignorance; we cannot reproduce all of the important papers that have helped in the evolution of fuzzy pattern recognition (there may be as many as five hundred) even in this narrow application domain. We will attempt, in each chapter introduction, to comment on some of the important papers that not been included and we ask both readers and authors to understand that a book such as this simply cannot {open_quotes}contain everything.{close_quotes} Our objective in Chapter 1 is to describe the basic structure of fuzzy sets theory as it applies to the major problems encountered in the design of a pattern recognition system.

  3. The Army word recognition system

    NASA Technical Reports Server (NTRS)

    Hadden, David R.; Haratz, David

    1977-01-01

    The application of speech recognition technology in the Army command and control area is presented. The problems associated with this program are described as well as as its relevance in terms of the man/machine interactions, voice inflexions, and the amount of training needed to interact with and utilize the automated system.

  4. Enduring voice recognition in bonobos

    PubMed Central

    Keenan, Sumir; Mathevon, Nicolas; Stevens, Jeroen MG; Guéry, Jean Pascal; Zuberbühler, Klaus; Levréro, Florence

    2016-01-01

    Long-term social recognition is vital for species with complex social networks, where familiar individuals can encounter one another after long periods of separation. For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. Vocal recognition after years of separation has never been reported in any great ape species, despite their complex societies and advanced social intelligence. Here we show that bonobos, Pan paniscus, demonstrate reliable vocal recognition of social partners, even if they have been separated for five years. We experimentally tested bonobos’ responses to the calls of previous group members that had been transferred between captive groups. Despite long separations, subjects responded more intensely to familiar voices than to calls from unknown individuals - the first experimental evidence that bonobos can identify individuals utilising vocalisations even years after their last encounter. Our study also suggests that bonobos may cease to discriminate between familiar and unfamiliar individuals after a period of eight years, indicating that voice representations or interest could be limited in time in this species. PMID:26911199

  5. Enduring voice recognition in bonobos.

    PubMed

    Keenan, Sumir; Mathevon, Nicolas; Stevens, Jeroen M G; Guéry, Jean Pascal; Zuberbühler, Klaus; Levréro, Florence

    2016-01-01

    Long-term social recognition is vital for species with complex social networks, where familiar individuals can encounter one another after long periods of separation. For non-human primates who live in dense forest environments, visual access to one another is often limited, and recognition of social partners over distances largely depends on vocal communication. Vocal recognition after years of separation has never been reported in any great ape species, despite their complex societies and advanced social intelligence. Here we show that bonobos, Pan paniscus, demonstrate reliable vocal recognition of social partners, even if they have been separated for five years. We experimentally tested bonobos' responses to the calls of previous group members that had been transferred between captive groups. Despite long separations, subjects responded more intensely to familiar voices than to calls from unknown individuals - the first experimental evidence that bonobos can identify individuals utilising vocalisations even years after their last encounter. Our study also suggests that bonobos may cease to discriminate between familiar and unfamiliar individuals after a period of eight years, indicating that voice representations or interest could be limited in time in this species. PMID:26911199

  6. Output Interference in Recognition Memory

    ERIC Educational Resources Information Center

    Criss, Amy H.; Malmberg, Kenneth J.; Shiffrin, Richard M.

    2011-01-01

    Dennis and Humphreys (2001) proposed that interference in recognition memory arises solely from the prior contexts of the test word: Interference does not arise from memory traces of other words (from events prior to the study list or on the study list, and regardless of similarity to the test item). We evaluate this model using output…

  7. Low-resolution gait recognition.

    PubMed

    Zhang, Junping; Pu, Jian; Chen, Changyou; Fleischer, Rudolf

    2010-08-01

    Unlike other biometric authentication methods, gait recognition is noninvasive and effective from a distance. However, the performance of gait recognition will suffer in the low-resolution (LR) case. Furthermore, when gait sequences are projected onto a nonoptimal low-dimensional subspace to reduce the data complexity, the performance of gait recognition will also decline. To deal with these two issues, we propose a new algorithm called superresolution with manifold sampling and backprojection (SRMS), which learns the high-resolution (HR) counterparts of LR test images from a collection of HR/LR training gait image patch pairs. Then, we incorporate SRMS into a new algorithm called multilinear tensor-based learning without tuning parameters (MTP) for LR gait recognition. Our contributions include the following: 1) With manifold sampling, the redundancy of gait image patches is remarkably decreased; thus, the superresolution procedure is more efficient and reasonable. 2) Backprojection guarantees that the learned HR gait images and the corresponding LR gait images can be more consistent. 3) The optimal subspace dimension for dimension reduction is automatically determined without introducing extra parameters. 4) Theoretical analysis of the algorithm shows that MTP converges. Experiments on the USF human gait database and the CASIA gait database show the increased efficiency of the proposed algorithm, compared with previous algorithms. PMID:20199936

  8. Neural networks for handwriting recognition

    NASA Astrophysics Data System (ADS)

    Kelly, David A.

    1992-09-01

    The market for a product that can read handwritten forms, such as insurance applications, re- order forms, or checks, is enormous. Companies could save millions of dollars each year if they had an effective and efficient way to read handwritten forms into a computer without human intervention. Urged on by the potential gold mine that an adequate solution would yield, a number of companies and researchers have developed, and are developing, neural network-based solutions to this long-standing problem. This paper briefly outlines the current state-of-the-art in neural network-based handwriting recognition research and products. The first section of the paper examines the potential market for this technology. The next section outlines the steps in the recognition process, followed by a number of the basic issues that need to be dealt with to solve the recognition problem in a real-world setting. Next, an overview of current commercial solutions and research projects shows the different ways that neural networks are applied to the problem. This is followed by a breakdown of the current commercial market and the future outlook for neural network-based handwriting recognition technology.

  9. Picture Details in Recognition Memory.

    ERIC Educational Resources Information Center

    Cody, James A.; Madigan, Stephen

    A study was conducted to investigate the effects of symbolic format of test material on short- and long-term recognition. Subjects, 104 undergraduate students, viewed slides of either a black-and-white photograph, a one-sentence verbal description of the photo, a black-and-white drawing based on the verbal description, or a black-and-white line…

  10. Object recognition memory in zebrafish.

    PubMed

    May, Zacnicte; Morrill, Adam; Holcombe, Adam; Johnston, Travis; Gallup, Joshua; Fouad, Karim; Schalomon, Melike; Hamilton, Trevor James

    2016-01-01

    The novel object recognition, or novel-object preference (NOP) test is employed to assess recognition memory in a variety of organisms. The subject is exposed to two identical objects, then after a delay, it is placed back in the original environment containing one of the original objects and a novel object. If the subject spends more time exploring one object, this can be interpreted as memory retention. To date, this test has not been fully explored in zebrafish (Danio rerio). Zebrafish possess recognition memory for simple 2- and 3-dimensional geometrical shapes, yet it is unknown if this translates to complex 3-dimensional objects. In this study we evaluated recognition memory in zebrafish using complex objects of different sizes. Contrary to rodents, zebrafish preferentially explored familiar over novel objects. Familiarity preference disappeared after delays of 5 mins. Leopard danios, another strain of D. rerio, also preferred the familiar object after a 1 min delay. Object preference could be re-established in zebra danios by administration of nicotine tartrate salt (50mg/L) prior to stimuli presentation, suggesting a memory-enhancing effect of nicotine. Additionally, exploration biases were present only when the objects were of intermediate size (2 × 5 cm). Our results demonstrate zebra and leopard danios have recognition memory, and that low nicotine doses can improve this memory type in zebra danios. However, exploration biases, from which memory is inferred, depend on object size. These findings suggest zebrafish ecology might influence object preference, as zebrafish neophobia could reflect natural anti-predatory behaviour. PMID:26376244

  11. Public domain optical character recognition

    NASA Astrophysics Data System (ADS)

    Garris, Michael D.; Blue, James L.; Candela, Gerald T.; Dimmick, Darrin L.; Geist, Jon C.; Grother, Patrick J.; Janet, Stanley A.; Wilson, Charles L.

    1995-03-01

    A public domain document processing system has been developed by the National Institute of Standards and Technology (NIST). The system is a standard reference form-based handprint recognition system for evaluating optical character recognition (OCR), and it is intended to provide a baseline of performance on an open application. The system's source code, training data, performance assessment tools, and type of forms processed are all publicly available. The system recognizes the handprint entered on handwriting sample forms like the ones distributed with NIST Special Database 1. From these forms, the system reads hand-printed numeric fields, upper and lowercase alphabetic fields, and unconstrained text paragraphs comprised of words from a limited-size dictionary. The modular design of the system makes it useful for component evaluation and comparison, training and testing set validation, and multiple system voting schemes. The system contains a number of significant contributions to OCR technology, including an optimized probabilistic neural network (PNN) classifier that operates a factor of 20 times faster than traditional software implementations of the algorithm. The source code for the recognition system is written in C and is organized into 11 libraries. In all, there are approximately 19,000 lines of code supporting more than 550 subroutines. Source code is provided for form registration, form removal, field isolation, field segmentation, character normalization, feature extraction, character classification, and dictionary-based postprocessing. The recognition system has been successfully compiled and tested on a host of UNIX workstations. This paper gives an overview of the recognition system's software architecture, including descriptions of the various system components along with timing and accuracy statistics.

  12. Context Effects and Retrieval in Recognition Memory

    ERIC Educational Resources Information Center

    Paul, Lawrence M.; And Others

    1975-01-01

    Describes an experiment designed to test predictions derived from a model of recognition memory that assumes no retrieval processes. It is argued that context effects do not necessarily imply retrieval processes in recognition. (Author/AM)

  13. Speech Recognition: Its Place in Business Education.

    ERIC Educational Resources Information Center

    Szul, Linda F.; Bouder, Michele

    2003-01-01

    Suggests uses of speech recognition devices in the classroom for students with disabilities. Compares speech recognition software packages and provides guidelines for selection and teaching. (Contains 14 references.) (SK)

  14. Method and System for Object Recognition Search

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A. (Inventor); Duong, Vu A. (Inventor); Stubberud, Allen R. (Inventor)

    2012-01-01

    A method for object recognition using shape and color features of the object to be recognized. An adaptive architecture is used to recognize and adapt the shape and color features for moving objects to enable object recognition.

  15. 8 CFR 1292.2 - Organizations qualified for recognition; requests for recognition; withdrawal of recognition...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... Section 1292.2 Aliens and Nationality EXECUTIVE OFFICE FOR IMMIGRATION REVIEW, DEPARTMENT OF JUSTICE IMMIGRATION REGULATIONS REPRESENTATION AND APPEARANCES § 1292.2 Organizations qualified for recognition... Immigration Court). Such organization must establish to the satisfaction of the Board that: (1) It makes...

  16. 77 FR 9590 - Recognition and Accreditation

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-17

    ...; ] DEPARTMENT OF JUSTICE 8 CFR Part 1292 RIN 1125-AA72 Recognition and Accreditation AGENCY: Executive Office... the recognition of organizations and accreditation of representatives who appear before EOIR. EOIR... discuss these regulations. The first meeting will be limited to a discussion of the recognition...

  17. Natural Language Processing: Word Recognition without Segmentation.

    ERIC Educational Resources Information Center

    Saeed, Khalid; Dardzinska, Agnieszka

    2001-01-01

    Discussion of automatic recognition of hand and machine-written cursive text using the Arabic alphabet focuses on an algorithm for word recognition. Describes results of testing words for recognition without segmentation and considers the algorithms' use for words of different fonts and for processing whole sentences. (Author/LRW)

  18. Examining the Relationships among Item Recognition, Source Recognition, and Recall from an Individual Differences Perspective

    ERIC Educational Resources Information Center

    Unsworth, Nash; Brewer, Gene A.

    2009-01-01

    The authors of the current study examined the relationships among item-recognition, source-recognition, free recall, and other memory and cognitive ability tasks via an individual differences analysis. Two independent sources of variance contributed to item-recognition and source-recognition performance, and these two constructs related…

  19. Intelligent word-based text recognition

    NASA Astrophysics Data System (ADS)

    Hoenes, Frank; Bleisinger, Rainer; Dengel, Andreas R.

    1991-02-01

    STRACT The need for making information within paper documents available for computers increases steadily. In this paper we present a system which is capable to read and to simply understand address blocks of business letters. It is based on optical word recognition (OWR) techniques uses feature recognition methods based on word shapes and is largly independent from different fonts and sizes. Even uncertainly recognized words can be identified using a dictionary and a specific verification algorithm. Additionally recognition accuracy is improved considering different knowledge layers like address syntax and logical dictionaries. Keywords: Text recognition document layout classification text analysis pattern recognition intelligent interfaces

  20. Covert face recognition without prosopagnosia.

    PubMed

    Ellis, H D; Young, A W; Koenken, G

    1993-01-01

    An experiment is reported where subjects were presented with familiar or unfamiliar faces for supraliminal durations or for durations individually assessed as being below the threshold for recognition. Their electrodermal responses to each stimulus were measured and the results showed higher peak amplitude skin conductance responses for familiar than for unfamiliar faces, regardless of whether they had been displayed supraliminally or subliminally. A parallel is drawn between elevated skin conductance responses to subliminal stimuli and findings of covert recognition of familiar faces in prosopagnosic patients, some of whom show increased electrodermal activity (EDA) to previously familiar faces. The supraliminal presentation data also served to replicate similar work by Tranel et al (1985). The results are considered alongside other data indicating the relation between non-conscious, "automatic" aspects of normal visual information processing and abilities which can be found to be preserved without awareness after brain injury. PMID:24487927

  1. Molecular Recognition and Ligand Association

    NASA Astrophysics Data System (ADS)

    Baron, Riccardo; McCammon, J. Andrew

    2013-04-01

    We review recent developments in our understanding of molecular recognition and ligand association, focusing on two major viewpoints: (a) studies that highlight new physical insight into the molecular recognition process and the driving forces determining thermodynamic signatures of binding and (b) recent methodological advances in applications to protein-ligand binding. In particular, we highlight the challenges posed by compensating enthalpic and entropic terms, competing solute and solvent contributions, and the relevance of complex configurational ensembles comprising multiple protein, ligand, and solvent intermediate states. As more complete physics is taken into account, computational approaches increase their ability to complement experimental measurements, by providing a microscopic, dynamic view of ensemble-averaged experimental observables. Physics-based approaches are increasingly expanding their power in pharmacology applications.

  2. PHYSICAL MODEL FOR RECOGNITION TUNNELING

    PubMed Central

    Krstić, Predrag; Ashcroft, Brian; Lindsay, Stuart

    2015-01-01

    Recognition tunneling (RT) identifies target molecules trapped between tunneling electrodes functionalized with recognition molecules that serve as specific chemical linkages between the metal electrodes and the trapped target molecule. Possible applications include single molecule DNA and protein sequencing. This paper addresses several fundamental aspects of RT by multiscale theory, applying both all-atom and coarse-grained DNA models: (1) We show that the magnitude of the observed currents are consistent with the results of non-equilibrium Green's function calculations carried out on a solvated all-atom model. (2) Brownian fluctuations in hydrogen bond-lengths lead to current spikes that are similar to what is observed experimentally. (3) The frequency characteristics of these fluctuations can be used to identify the trapped molecules with a machine-learning algorithm, giving a theoretical underpinning to this new method of identifying single molecule signals. PMID:25650375

  3. Automatic Recognition of Road Signs

    NASA Astrophysics Data System (ADS)

    Inoue, Yasuo; Kohashi, Yuuichirou; Ishikawa, Naoto; Nakajima, Masato

    2002-11-01

    The increase in traffic accidents is becoming a serious social problem with the recent rapid traffic increase. In many cases, the driver"s carelessness is the primary factor of traffic accidents, and the driver assistance system is demanded for supporting driver"s safety. In this research, we propose the new method of automatic detection and recognition of road signs by image processing. The purpose of this research is to prevent accidents caused by driver"s carelessness, and call attention to a driver when the driver violates traffic a regulation. In this research, high accuracy and the efficient sign detecting method are realized by removing unnecessary information except for a road sign from an image, and detect a road sign using shape features. At first, the color information that is not used in road signs is removed from an image. Next, edges except for circular and triangle ones are removed to choose sign shape. In the recognition process, normalized cross correlation operation is carried out to the two-dimensional differentiation pattern of a sign, and the accurate and efficient method for detecting the road sign is realized. Moreover, the real-time operation in a software base was realized by holding down calculation cost, maintaining highly precise sign detection and recognition. Specifically, it becomes specifically possible to process by 0.1 sec(s)/frame using a general-purpose PC (CPU: Pentium4 1.7GHz). As a result of in-vehicle experimentation, our system could process on real time and has confirmed that detection and recognition of a sign could be performed correctly.

  4. Organizing multivalency in carbohydrate recognition.

    PubMed

    Müller, Christian; Despras, Guillaume; Lindhorst, Thisbe K

    2016-06-01

    The interactions of cell surface carbohydrates as well as of soluble glycoconjugates with their receptor proteins rule fundamental processes in cell biology. One of the supramolecular principles underlying and regulating carbohydrate recognition is multivalency. Many multivalent glycoconjugates have therefore been synthesized to study multivalency effects operative in glycobiology. This review is focused on smaller multivalent structures such as glycoclusters emphasizing carbohydrate-centered and heteromultivalent glycoconjugates. We are discussing primary, secondary and tertiary structural aspects including approaches to organize multivalency. PMID:27146554

  5. Image processing for drawing recognition

    NASA Astrophysics Data System (ADS)

    Feyzkhanov, Rustem; Zhelavskaya, Irina

    2014-03-01

    The task of recognizing edges of rectangular structures is well known. Still, almost all of them work with static images and has no limit on work time. We propose application of conducting homography for the video stream which can be obtained from the webcam. We propose algorithm which can be successfully used for this kind of application. One of the main use cases of such application is recognition of drawings by person on the piece of paper before webcam.

  6. Immune recognition of citrullinated epitopes.

    PubMed

    Nguyen, Hai; James, Eddie A

    2016-10-01

    Conversion of arginine into citrulline is a post-translational modification that is observed in normal physiological processes. However, abnormal citrullination can provoke autoimmunity by generating altered self-epitopes that are specifically targeted by autoantibodies and T cells. In this review we discuss the recognition of citrullinated antigens in human autoimmune diseases and the role that this modification plays in increasing antigenic diversity and circumventing tolerance mechanisms. Early published work demonstrated that citrullinated proteins are specifically targeted by autoantibodies in rheumatoid arthritis and that citrullinated peptides are more readily presented to T cells by arthritis-susceptible HLA class II 'shared epitope' proteins. Emerging data support the relevance of citrullinated epitopes in other autoimmune diseases, including type 1 diabetes and multiple sclerosis, whose susceptible HLA haplotypes also preferentially present citrullinated peptides. In these settings, autoimmune patients have been shown to have elevated responses to citrullinated epitopes derived from tissue-specific antigens. Contrasting evidence implicates autophagy or perforin and complement-mediated membrane attack as inducers of ectopic citrullination. In either case, the peptidyl deiminases responsible for citrullination are activated in response to inflammation or insult, providing a mechanistic link between this post-translational modification and interactions with the environment and infection. As such, it is likely that immune recognition of citrullinated epitopes also plays a role in pathogen clearance. Indeed, our recent data suggest that responses to citrullinated peptides facilitate recognition of novel influenza strains. Therefore, increased understanding of responses to citrullinated epitopes may provide important insights about the initiation of autoimmunity and recognition of heterologous viruses. PMID:27531825

  7. Associative Interference and Recognition Memory.

    ERIC Educational Resources Information Center

    Underwood, Benton J.; And Others

    Three experiments tested the generality of the conclusion that associative unlearning is minimal in the A-B, A-D paradigm. In Experiment 1, single-trial study of A-D, following single-trial study of A-B, did not produce retroactive inhibition in the recognition of A-B. In Experiment 2, A-B was acquired by associative matching. The interpolated…

  8. Automatic speech recognition technology development at ITT Defense Communications Division

    NASA Technical Reports Server (NTRS)

    White, George M.

    1977-01-01

    An assessment of the applications of automatic speech recognition to defense communication systems is presented. Future research efforts include investigations into the following areas: (1) dynamic programming; (2) recognition of speech degraded by noise; (3) speaker independent recognition; (4) large vocabulary recognition; (5) word spotting and continuous speech recognition; and (6) isolated word recognition.

  9. Visual recognition of permuted words

    NASA Astrophysics Data System (ADS)

    Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

    2010-02-01

    In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

  10. Human recognition of familiar voices.

    PubMed

    Wenndt, Stanley J

    2016-08-01

    Recognizing familiar voices is something we do every day. In quiet environments, it is usually easy to recognize a familiar voice. In noisier environments, this can become a difficult task. This paper examines how robust listeners are at identifying familiar voices in noisy, changing environments and what factors may affect their recognition rates. While there is previous research addressing familiar speaker recognition, the research is limited due to the difficulty in obtaining appropriate data that eliminates speaker dependent traits, such as word choice, along with having corresponding listeners who are familiar with the speakers. The data used in this study were collected in such a fashion to mimic conversational, free-flow dialogue, but in a way to eliminate many variables such as word choice, intonation, or non-verbal cues. These data provide some of the most realistic test scenarios to-date for familiar speaker identification. A pure-tone hearing test was used to separate listeners into normal hearing and hearing impaired groups. It is hypothesized that the results of the Normal Hearing Group will be statistically better. Additionally, the aspect of familiar speaker recognition is addressed by having each listener rate his or her familiarity with each speaker. Two statistical approaches showed that the more familiar a listener is with a speaker, the more likely the listener will recognize the speaker. PMID:27586746

  11. Fingerprint recognition using image processing

    NASA Astrophysics Data System (ADS)

    Dholay, Surekha; Mishra, Akassh A.

    2011-06-01

    Finger Print Recognition is concerned with the difficult task of matching the images of finger print of a person with the finger print present in the database efficiently. Finger print Recognition is used in forensic science which helps in finding the criminals and also used in authentication of a particular person. Since, Finger print is the only thing which is unique among the people and changes from person to person. The present paper describes finger print recognition methods using various edge detection techniques and also how to detect correct finger print using a camera images. The present paper describes the method that does not require a special device but a simple camera can be used for its processes. Hence, the describe technique can also be using in a simple camera mobile phone. The various factors affecting the process will be poor illumination, noise disturbance, viewpoint-dependence, Climate factors, and Imaging conditions. The described factor has to be considered so we have to perform various image enhancement techniques so as to increase the quality and remove noise disturbance of image. The present paper describe the technique of using contour tracking on the finger print image then using edge detection on the contour and after that matching the edges inside the contour.

  12. Disordered recognition memory: recollective confabulation.

    PubMed

    Moulin, Chris J A

    2013-06-01

    Recollective confabulation (RC) is encountered as a conviction that a present moment is a repetition of one experienced previously, combined with the retrieval of confabulated specifics to support that assertion. It is often described as persistent déjà vu by family members and caregivers. On formal testing, patients with RC tend to produce a very high level of false positive errors. In this paper, a new case series of 11 people with dementia or mild cognitive impairment (MCI) and with déjà vu-like experiences is presented. In two experiments the nature of the recognition memory deficit is explored. The results from these two experiments suggest - contrary to our hypothesis in earlier published case reports - that recollection mechanisms are relatively spared in this group, and that patients experience familiarity for non-presented items. The RC patients tended to be overconfident in their assessment of recognition memory, and produce inaccurate assessments of their performance. These findings are discussed with reference to delusions more generally, and point to a combined memory and metacognitive deficit, possibly arising from damage to temporal and right frontal regions. It is proposed that RC arises from a metacognitive error; an attempt to justify inappropriate feelings of familiarity which leads to false recognition. PMID:23507236

  13. Additive attacks on speaker recognition

    NASA Astrophysics Data System (ADS)

    Farrokh Baroughi, Alireza; Craver, Scott

    2014-02-01

    Speaker recognition is used to identify a speaker's voice from among a group of known speakers. A common method of speaker recognition is a classification based on cepstral coefficients of the speaker's voice, using a Gaussian mixture model (GMM) to model each speaker. In this paper we try to fool a speaker recognition system using additive noise such that an intruder is recognized as a target user. Our attack uses a mixture selected from a target user's GMM model, inverting the cepstral transformation to produce noise samples. In our 5 speaker data base, we achieve an attack success rate of 50% with a noise signal at 10dB SNR, and 95% by increasing noise power to 0dB SNR. The importance of this attack is its simplicity and flexibility: it can be employed in real time with no processing of an attacker's voice, and little computation is needed at the moment of detection, allowing the attack to be performed by a small portable device. For any target user, knowing that user's model or voice sample is sufficient to compute the attack signal, and it is enough that the intruder plays it while he/she is uttering to be classiffed as the victim.

  14. Infant Visual Attention and Object Recognition

    PubMed Central

    Reynolds, Greg D.

    2015-01-01

    This paper explores the role visual attention plays in the recognition of objects in infancy. Research and theory on the development of infant attention and recognition memory are reviewed in three major sections. The first section reviews some of the major findings and theory emerging from a rich tradition of behavioral research utilizing preferential looking tasks to examine visual attention and recognition memory in infancy. The second section examines research utilizing neural measures of attention and object recognition in infancy as well as research on brain-behavior relations in the early development of attention and recognition memory. The third section addresses potential areas of the brain involved in infant object recognition and visual attention. An integrated synthesis of some of the existing models of the development of visual attention is presented which may account for the observed changes in behavioral and neural measures of visual attention and object recognition that occur across infancy. PMID:25596333

  15. Acquired prosopagnosia without word recognition deficits.

    PubMed

    Susilo, Tirta; Wright, Victoria; Tree, Jeremy J; Duchaine, Bradley

    2015-01-01

    It has long been suggested that face recognition relies on specialized mechanisms that are not involved in visual recognition of other object categories, including those that require expert, fine-grained discrimination at the exemplar level such as written words. But according to the recently proposed many-to-many theory of object recognition (MTMT), visual recognition of faces and words are carried out by common mechanisms [Behrmann, M., & Plaut, D. C. ( 2013 ). Distributed circuits, not circumscribed centers, mediate visual recognition. Trends in Cognitive Sciences, 17, 210-219]. MTMT acknowledges that face and word recognition are lateralized, but posits that the mechanisms that predominantly carry out face recognition still contribute to word recognition and vice versa. MTMT makes a key prediction, namely that acquired prosopagnosics should exhibit some measure of word recognition deficits. We tested this prediction by assessing written word recognition in five acquired prosopagnosic patients. Four patients had lesions limited to the right hemisphere while one had bilateral lesions with more pronounced lesions in the right hemisphere. The patients completed a total of seven word recognition tasks: two lexical decision tasks and five reading aloud tasks totalling more than 1200 trials. The performances of the four older patients (3 female, age range 50-64 years) were compared to those of 12 older controls (8 female, age range 56-66 years), while the performances of the younger prosopagnosic (male, 31 years) were compared to those of 14 younger controls (9 female, age range 20-33 years). We analysed all results at the single-patient level using Crawford's t-test. Across seven tasks, four prosopagnosics performed as quickly and accurately as controls. Our results demonstrate that acquired prosopagnosia can exist without word recognition deficits. These findings are inconsistent with a key prediction of MTMT. They instead support the hypothesis that face

  16. Recognition.

    ERIC Educational Resources Information Center

    Bowen, John; Wildasin, Michael; Chaltain, Sam

    2002-01-01

    Tells about schools rewarded for upholding First Amendment protections. Discusses the Let Freedom Ring Award. Considers how even the prestige and honor associated with winning national awards for freedom in the schools does not guarantee success in the ongoing fight to practice what the United States Constitution guarantees and educational logic…

  17. Neural network and letter recognition

    SciTech Connect

    Lee, Hue Yeon.

    1989-01-01

    Neural net architectures and learning algorithms that recognize hand written 36 alphanumeric characters are studied. The thin line input patterns written in 32 x 32 binary array are used. The system is comprised of two major components, viz. a preprocessing unit and a Recognition unit. The preprocessing unit in turn consists of three layers of neurons; the U-layer, the V-layer, and the C-layer. The functions of the U-layer is to extract local features by template matching. The correlation between the detected local features are considered. Through correlating neurons in a plane with their neighboring neurons, the V-layer would thicken the on-cells or lines that are groups of on-cells of the previous layer. These two correlations would yield some deformation tolerance and some of the rotational tolerance of the system. The C-layer then compresses data through the Gabor transform. Pattern dependent choice of center and wavelengths of Gabor filters is the cause of shift and scale tolerance of the system. Three different learning schemes had been investigated in the recognition unit, namely; the error back propagation learning with hidden units, a simple perceptron learning, and a competitive learning. Their performances were analyzed and compared. Since sometimes the network fails to distinguish between two letters that are inherently similar, additional ambiguity resolving neural nets are introduced on top of the above main neural net. The two dimensional Fourier transform is used as the preprocessing and the perceptron is used as the recognition unit of the ambiguity resolver. One hundred different person's handwriting sets are collected. Some of these are used as the training sets and the remainders are used as the test sets.

  18. Intralist interference in recognition memory.

    PubMed

    Kim, K; Glanzer, M

    1995-09-01

    Three experiments on recognition memory were carried out to define the nature of intralist interference effects. Experiment 1 replicated the findings of an earlier study (A. I. Schulman, 1971) on what appeared to be combined study (input) and test (output) order effects and added information on the presence of speed-accuracy trade-off effects. Experiment 2 demonstrated that only test order was effective and that study order effects did not occur. Experiment 3 demonstrated again that only test order was effective and also showed that the effect remained when response times were controlled. Attention/likelihood theory was fitted to the data of the final, clarified interference effect. PMID:8744957

  19. Speech recognition technology: a critique.

    PubMed Central

    Levinson, S E

    1995-01-01

    This paper introduces the session on advanced speech recognition technology. The two papers comprising this session argue that current technology yields a performance that is only an order of magnitude in error rate away from human performance and that incremental improvements will bring us to that desired level. I argue that, to the contrary, present performance is far removed from human performance and a revolution in our thinking is required to achieve the goal. It is further asserted that to bring about the revolution more effort should be expended on basic research and less on trying to prematurely commercialize a deficient technology. PMID:7479808

  20. Research in continuous speech recognition

    NASA Astrophysics Data System (ADS)

    Schwartz, R. M.; Chow, Y. L.; Makhoul, J.

    1983-12-01

    This annual report describes the work performed during the past year in an ongoing effort to design and implement a system that performs phonetic recognition of continuous speech. The general approach used it to develop a Hidden Markov Model (HMM) of speech parameter movements, which can be used to distinguish among the different phonemes. The resulting phoneme models incorporate the contextural effects of neighboring phonemes. One main aspect of this research is to incorporate both spectral parameters and acoustic-phonetic features into the HMM formalism.

  1. Transfer Learning for Activity Recognition: A Survey

    PubMed Central

    Cook, Diane; Feuz, Kyle D.; Krishnan, Narayanan C.

    2013-01-01

    Many intelligent systems that focus on the needs of a human require information about the activities being performed by the human. At the core of this capability is activity recognition, which is a challenging and well-researched problem. Activity recognition algorithms require substantial amounts of labeled training data yet need to perform well under very diverse circumstances. As a result, researchers have been designing methods to identify and utilize subtle connections between activity recognition datasets, or to perform transfer-based activity recognition. In this paper we survey the literature to highlight recent advances in transfer learning for activity recognition. We characterize existing approaches to transfer-based activity recognition by sensor modality, by differences between source and target environments, by data availability, and by type of information that is transferred. Finally, we present some grand challenges for the community to consider as this field is further developed. PMID:24039326

  2. Kannada character recognition system using neural network

    NASA Astrophysics Data System (ADS)

    Kumar, Suresh D. S.; Kamalapuram, Srinivasa K.; Kumar, Ajay B. R.

    2013-03-01

    Handwriting recognition has been one of the active and challenging research areas in the field of pattern recognition. It has numerous applications which include, reading aid for blind, bank cheques and conversion of any hand written document into structural text form. As there is no sufficient number of works on Indian language character recognition especially Kannada script among 15 major scripts in India. In this paper an attempt is made to recognize handwritten Kannada characters using Feed Forward neural networks. A handwritten Kannada character is resized into 20x30 Pixel. The resized character is used for training the neural network. Once the training process is completed the same character is given as input to the neural network with different set of neurons in hidden layer and their recognition accuracy rate for different Kannada characters has been calculated and compared. The results show that the proposed system yields good recognition accuracy rates comparable to that of other handwritten character recognition systems.

  3. Document recognition serving people with disabilities

    NASA Astrophysics Data System (ADS)

    Fruchterman, James R.

    2007-01-01

    Document recognition advances have improved the lives of people with print disabilities, by providing accessible documents. This invited paper provides perspectives on the author's career progression from document recognition professional to social entrepreneur applying this technology to help people with disabilities. Starting with initial thoughts about optical character recognition in college, it continues with the creation of accurate omnifont character recognition that did not require training. It was difficult to make a reading machine for the blind in a commercial setting, which led to the creation of a nonprofit social enterprise to deliver these devices around the world. This network of people with disabilities scanning books drove the creation of Bookshare.org, an online library of scanned books. Looking forward, the needs for improved document recognition technology to further lower the barriers to reading are discussed. Document recognition professionals should be proud of the positive impact their work has had on some of society's most disadvantaged communities.

  4. Speech recognition with amplitude and frequency modulations

    NASA Astrophysics Data System (ADS)

    Zeng, Fan-Gang; Nie, Kaibao; Stickney, Ginger S.; Kong, Ying-Yee; Vongphoe, Michael; Bhargave, Ashish; Wei, Chaogang; Cao, Keli

    2005-02-01

    Amplitude modulation (AM) and frequency modulation (FM) are commonly used in communication, but their relative contributions to speech recognition have not been fully explored. To bridge this gap, we derived slowly varying AM and FM from speech sounds and conducted listening tests using stimuli with different modulations in normal-hearing and cochlear-implant subjects. We found that although AM from a limited number of spectral bands may be sufficient for speech recognition in quiet, FM significantly enhances speech recognition in noise, as well as speaker and tone recognition. Additional speech reception threshold measures revealed that FM is particularly critical for speech recognition with a competing voice and is independent of spectral resolution and similarity. These results suggest that AM and FM provide independent yet complementary contributions to support robust speech recognition under realistic listening situations. Encoding FM may improve auditory scene analysis, cochlear-implant, and audiocoding performance. auditory analysis | cochlear implant | neural code | phase | scene analysis

  5. Characterization of molecular recognition in gas sensors

    SciTech Connect

    Hierlemann, A.; Ricco, A.J.; Bodenhoefer, K.; Goepel, W.

    1998-08-01

    Molecular recognition is an important topic when searching for new, selective coating materials for chemical sensing. Recently, the general idea of molecular recognition in the gas phase was challenged by Grate et al. However, in earlier thickness-shear mode resonator (TSMR) investigations, convincing evidence was presented for specific recognition of particular analyte target molecules. In this study, the authors systematically investigated coatings previously shown to be highly selective, such as the bucket-like cyclodextrins for chiral recognition, Ni-camphorates for the specific detection of the bases pyridine and DMMP (dimethylmethylphosphonate), and phthalocyanines to specifically detect benzene, toluene, and xylene (BTX).

  6. New method of 3-D object recognition

    NASA Astrophysics Data System (ADS)

    He, An-Zhi; Li, Qun Z.; Miao, Peng C.

    1991-12-01

    In this paper, a new method of 3-D object recognition using optical techniques and a computer is presented. We perform 3-D object recognition using moire contour to obtain the object's 3- D coordinates, projecting drawings of the object in three coordinate planes to describe it and using a method of inquiring library of judgement to match objects. The recognition of a simple geometrical entity is simulated by computer and studied experimentally. The recognition of an object which is composed of a few simple geometrical entities is discussed.

  7. Robust speech recognition from binary masks.

    PubMed

    Narayanan, Arun; Wang, DeLiang

    2010-11-01

    Inspired by recent evidence that a binary pattern may provide sufficient information for human speech recognition, this letter proposes a fundamentally different approach to robust automatic speech recognition. Specifically, recognition is performed by classifying binary masks corresponding to a word utterance. The proposed method is evaluated using a subset of the TIDigits corpus to perform isolated digit recognition. Despite dramatic reduction of speech information encoded in a binary mask, the proposed system performs surprisingly well. The system is compared with a traditional HMM based approach and is shown to perform well under low SNR conditions. PMID:21110529

  8. Ordinal measures for iris recognition.

    PubMed

    Sun, Zhenan; Tan, Tieniu

    2009-12-01

    Images of a human iris contain rich texture information useful for identity authentication. A key and still open issue in iris recognition is how best to represent such textural information using a compact set of features (iris features). In this paper, we propose using ordinal measures for iris feature representation with the objective of characterizing qualitative relationships between iris regions rather than precise measurements of iris image structures. Such a representation may lose some image-specific information, but it achieves a good trade-off between distinctiveness and robustness. We show that ordinal measures are intrinsic features of iris patterns and largely invariant to illumination changes. Moreover, compactness and low computational complexity of ordinal measures enable highly efficient iris recognition. Ordinal measures are a general concept useful for image analysis and many variants can be derived for ordinal feature extraction. In this paper, we develop multilobe differential filters to compute ordinal measures with flexible intralobe and interlobe parameters such as location, scale, orientation, and distance. Experimental results on three public iris image databases demonstrate the effectiveness of the proposed ordinal feature models. PMID:19834142

  9. Disruptive camouflage impairs object recognition.

    PubMed

    Webster, Richard J; Hassall, Christopher; Herdman, Chris M; Godin, Jean-Guy J; Sherratt, Thomas N

    2013-01-01

    Whether hiding from predators, or avoiding battlefield casualties, camouflage is widely employed to prevent detection. Disruptive coloration is a seemingly well-known camouflage mechanism proposed to function by breaking up an object's salient features (for example their characteristic outline), rendering objects more difficult to recognize. However, while a wide range of animals are thought to evade detection using disruptive patterns, there is no direct experimental evidence that disruptive coloration impairs recognition. Using humans searching for computer-generated moth targets, we demonstrate that the number of edge-intersecting patches on a target reduces the likelihood of it being detected, even at the expense of reduced background matching. Crucially, eye-tracking data show that targets with more edge-intersecting patches were looked at for longer periods prior to attack, and passed-over more frequently during search tasks. We therefore show directly that edge patches enhance survivorship by impairing recognition, confirming that disruptive coloration is a distinct camouflage strategy, not simply an artefact of background matching. PMID:24152693

  10. Longitudinal study of fingerprint recognition

    PubMed Central

    Yoon, Soweon; Jain, Anil K.

    2015-01-01

    Human identification by fingerprints is based on the fundamental premise that ridge patterns from distinct fingers are different (uniqueness) and a fingerprint pattern does not change over time (persistence). Although the uniqueness of fingerprints has been investigated by developing statistical models to estimate the probability of error in comparing two random samples of fingerprints, the persistence of fingerprints has remained a general belief based on only a few case studies. In this study, fingerprint match (similarity) scores are analyzed by multilevel statistical models with covariates such as time interval between two fingerprints in comparison, subject’s age, and fingerprint image quality. Longitudinal fingerprint records of 15,597 subjects are sampled from an operational fingerprint database such that each individual has at least five 10-print records over a minimum time span of 5 y. In regard to the persistence of fingerprints, the longitudinal analysis on a single (right index) finger demonstrates that (i) genuine match scores tend to significantly decrease when time interval between two fingerprints in comparison increases, whereas the change in impostor match scores is negligible; and (ii) fingerprint recognition accuracy at operational settings, nevertheless, tends to be stable as the time interval increases up to 12 y, the maximum time span in the dataset. However, the uncertainty of temporal stability of fingerprint recognition accuracy becomes substantially large if either of the two fingerprints being compared is of poor quality. The conclusions drawn from 10-finger fusion analysis coincide with the conclusions from single-finger analysis. PMID:26124106

  11. Innate Immune Recognition of EBV.

    PubMed

    Lünemann, Anna; Rowe, Martin; Nadal, David

    2015-01-01

    The ability of Epstein-Barr virus (EBV) to establish latency despite specific immune responses and to successfully persist lifelong in the human host shows that EBV has developed powerful strategies and mechanisms to exploit, evade, abolish, or downsize otherwise effective immune responses to ensure its own survival. This chapter focuses on current knowledge on innate immune responses against EBV and its evasion strategies for own benefit and summarizes the questions that remain to be tackled. Innate immune reactions against EBV originate both from the main target cells of EBV and from nontarget cells, which are elements of the innate immune system. Thus, we structured our review accordingly but with a particular focus on the innate recognition of EBV in its two stages in its life cycle, latent state and lytic replication. Specifically, we discuss (I) innate sensing and resulting innate immune responses against EBV by its main target cells, focusing on (i) EBV transmission between epithelial cells and B cells and their life cycle stages; and (ii) elements of innate immunity in EBV's target cells. Further, we debate (II) the innate recognition and resulting innate immune responses against EBV by cells other than the main target cells, focusing on (iii) myeloid cells: dendritic cells, monocytes, macrophages, and neutrophil granulocytes; and (iv) natural killer cells. Finally, we address (III) how EBV counteracts or exploits innate immunity in its latent and lytic life cycle stages, concentrating on (v) TLRs; (vi) EBERs; and (vii) microRNAs. PMID:26428378

  12. Dynamic chemistry of anion recognition

    SciTech Connect

    Custelcean, Radu

    2012-01-01

    In the past 40 years, anion recognition by synthetic receptors has grown into a rich and vibrant research topic, developing into a distinct branch of Supramolecular Chemistry. Traditional anion receptors comprise organic scaffolds functionalized with complementary binding groups that are assembled by multistep organic synthesis. Recently, a new approach to anion receptors has emerged, in which the host is dynamically self-assembled in the presence of the anionic guest, via reversible bond formation between functional building units. While coordination bonds were initially employed for the self-assembly of the anion hosts, more recent studies demonstrated that reversible covalent bonds can serve the same purpose. In both cases, due to their labile connections, the molecular constituents have the ability to assemble, dissociate, and recombine continuously, thereby creating a dynamic combinatorial library (DCL) of receptors. The anionic guests, through specific molecular recognition, may then amplify (express) the formation of a particular structure among all possible combinations (real or virtual) by shifting the equilibria involved towards the most optimal receptor. This approach is not limited to solution self-assembly, but is equally applicable to crystallization, where the fittest anion-binding crystal may be selected. Finally, the pros and cons of employing dynamic combinatorial chemistry (DCC) vs molecular design for developing anion receptors, and the implications of both approaches to selective anion separations, will be discussed.

  13. Script recognition--a review.

    PubMed

    Ghosh, Debashis; Dube, Tulika; Shivaprasad, Adamane P

    2010-12-01

    A variety of different scripts are used in writing languages throughout the world. In a multiscript, multilingual environment, it is essential to know the script used in writing a document before an appropriate character recognition and document analysis algorithm can be chosen. In view of this, several methods for automatic script identification have been developed so far. They mainly belong to two broad categories-structure-based and visual-appearance-based techniques. This survey report gives an overview of the different script identification methodologies under each of these categories. Methods for script identification in online data and video-texts are also presented. It is noted that the research in this field is relatively thin and still more research is to be done, particularly in the case of handwritten documents. PMID:20975114

  14. Place recognition using batlike sonar.

    PubMed

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-01-01

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. PMID:27481189

  15. Pattern recognition systems and procedures

    NASA Technical Reports Server (NTRS)

    Nelson, G. D.; Serreyn, D. V.

    1972-01-01

    The objectives of the pattern recognition tasks are to develop (1) a man-machine interactive data processing system; and (2) procedures to determine effective features as a function of time for crops and soils. The signal analysis and dissemination equipment, SADE, is being developed as a man-machine interactive data processing system. SADE will provide imagery and multi-channel analog tape inputs for digitation and a color display of the data. SADE is an essential tool to aid in the investigation to determine useful features as a function of time for crops and soils. Four related studies are: (1) reliability of the multivariate Gaussian assumption; (2) usefulness of transforming features with regard to the classifier probability of error; (3) advantage of selecting quantizer parameters to minimize the classifier probability of error; and (4) advantage of using contextual data. The study of transformation of variables (features), especially those experimental studies which can be completed with the SADE system, will be done.

  16. Opportunity recognition in complex environments

    SciTech Connect

    Pryor, L.

    1996-12-31

    An agent operating in an unpredictable world must be able to take advantage of opportunities but cannot afford to perform a detailed analysis of the effects of every nuance of the current situation on its goals if it is to respond in a timely manner. This paper describes a filtering mechanism that enables the effective recognition of opportunities. The mechanism is based on a characterization of the world in terms of reference features, features that are both cheap and functional and that appear to be prevalent in everyday life. Its use enables the plan execution system PARETO to recognize types of opportunities that other systems cannot. Reference features can also play a role in the detection of threats, and may be involved in the development of expertise.

  17. Using Maintenance Rehearsal to Explore Recognition Memory

    ERIC Educational Resources Information Center

    Humphreys, Michael S.; Maguire, Angela M.; McFarlane, Kimberley A.; Burt, Jennifer S.; Bolland, Scott W.; Murray, Krista L.; Dunn, Ryan

    2010-01-01

    We examined associative and item recognition using the maintenance rehearsal paradigm. Our intent was to control for mnemonic strategies; to produce a low, graded level of learning; and to provide evidence of the role of attention in long-term memory. An advantage for low-frequency words emerged in both associative and item recognition at very low…

  18. Distortion invariant pattern recognition with phase filters

    NASA Technical Reports Server (NTRS)

    Rosen, Joseph; Shamir, Joseph

    1987-01-01

    A recently developed approach for pattern recognition using spatial filters with reduced tolerance requirements is employed for the generation of filters containing mainly phase information. As anticipated, the recognition levels were decreased, but they remain adequate for unambiguous identification together with appreciable amounts of distortion immunity. Furthermore, the information content of the filters is compatible with low devices like spatial light modulators.

  19. Optical Pattern Recognition With Self-Amplification

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang

    1994-01-01

    In optical pattern recognition system with self-amplification, no reference beam used in addressing mode. Polarization of laser beam and orientation of photorefractive crystal chosen to maximize photorefractive effect. Intensity of recognition signal is orders of magnitude greater than other optical correlators. Apparatus regarded as real-time or quasi-real-time optical pattern recognizer with memory and reprogrammability.

  20. Object Recognition Memory and the Rodent Hippocampus

    ERIC Educational Resources Information Center

    Broadbent, Nicola J.; Gaskin, Stephane; Squire, Larry R.; Clark, Robert E.

    2010-01-01

    In rodents, the novel object recognition task (NOR) has become a benchmark task for assessing recognition memory. Yet, despite its widespread use, a consensus has not developed about which brain structures are important for task performance. We assessed both the anterograde and retrograde effects of hippocampal lesions on performance in the NOR…

  1. Development of Strategies for Recall and Recognition

    ERIC Educational Resources Information Center

    Tversky, Barbara; Teiffer, Evelyn

    1976-01-01

    A total of 122 kindergartners, third and fifth graders viewed 30 pictures of familiar objects and interested on their free recall of the object names and their recognition of the original pictures. Half received instruction in adult recognition strategies, half in adult recall strategies. (MS)

  2. Performing speech recognition research with hypercard

    NASA Technical Reports Server (NTRS)

    Shepherd, Chip

    1993-01-01

    The purpose of this paper is to describe a HyperCard-based system for performing speech recognition research and to instruct Human Factors professionals on how to use the system to obtain detailed data about the user interface of a prototype speech recognition application.

  3. Robotic CCD microscope for enhanced crystal recognition

    DOEpatents

    Segelke, Brent W.; Toppani, Dominique

    2007-11-06

    A robotic CCD microscope and procedures to automate crystal recognition. The robotic CCD microscope and procedures enables more accurate crystal recognition, leading to fewer false negative and fewer false positives, and enable detection of smaller crystals compared to other methods available today.

  4. Online Handwriting Recognition for Indic Scripts

    NASA Astrophysics Data System (ADS)

    Bharath, A.; Madhvanath, Sriganesh

    Online handwriting recognition refers to the problem of machine recognition of handwriting captured in the form of pen trajectories. The recognition technology holds significant promise for Indic scripts, given that the Indic languages are used by a sixth of the world’s population, and the greater ease of use of handwriting-based text input for these scripts compared to keyboard-based methods. Even though the recognition of handwritten Devanagari, Bangla, and Tamil has received significant attention in recent times, one may say that research efforts directed at Indic script recognition in general are in their early stages. The structure of the scripts and the variety of shapes and writing styles pose challenges that are different from other scripts and hence require customized techniques for feature representation and recognition. In this chapter, we describe the challenges in recognizing online handwriting in Indic scripts and provide an overview of the state of the art for isolated character and word recognition. We then present in brief some of the promising applications, starting with handwriting-based text input systems (IMEs) that have been built for entering Indic scripts. In the last section, we provide a few pointers to resources such as tools and data sets that are currently available for online Indic script recognition research. endabstract

  5. Sources of Interference in Recognition Testing

    ERIC Educational Resources Information Center

    Annis, Jeffrey; Malmberg, Kenneth J.; Criss, Amy H.; Shiffrin, Richard M.

    2013-01-01

    Recognition memory accuracy is harmed by prior testing (a.k.a., output interference [OI]; Tulving & Arbuckle, 1966). In several experiments, we interpolated various tasks between recognition test trials. The stimuli and the tasks were more similar (lexical decision [LD] of words and nonwords) or less similar (gender identification of male and…

  6. Recognition without Awareness: Encoding and Retrieval Factors

    ERIC Educational Resources Information Center

    Craik, Fergus I. M.; Rose, Nathan S.; Gopie, Nigel

    2015-01-01

    The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The…

  7. The Status of Voice Recognition Technology.

    ERIC Educational Resources Information Center

    Miller, Ruth

    1986-01-01

    After examining the historical view of voice recognition, voice recognition technology today, the future of this technology, and information processing applications, the author states that educators must begin to prepare for tomorrow's technology now by researching current literature, analyzing hardware and software needs, and emphasizing oral…

  8. Voice Recognition: A New Assessment Tool?

    ERIC Educational Resources Information Center

    Jones, Darla

    2005-01-01

    This article presents the results of a study conducted in Anchorage, Alaska, that evaluated the accuracy and efficiency of using voice recognition (VR) technology to collect oral reading fluency data for classroom-based assessments. The primary research question was as follows: Is voice recognition technology a valid and reliable alternative to…

  9. Recognition hypermnesia: how to get it.

    PubMed

    Bergstein, Jacquelyn; Erdelyi, Matthew

    2008-10-01

    Although recall hypermnesia (enhanced recall) over time with repeated testing has by now become an established empirical fact, its recognition counterpart, recognition hypermnesia, has defied clear-cut laboratory confirmation. In four studies, which relied on the retrieval component of recognition memory, it was shown that recognition memory, indexed by d', reliably improved over three successive recognition tests. The stimuli consisted of 140 cartoons, each comprising a picture and a verbal caption. Recognition memory was tested on transforms or part-forms (parts) of the original stimulus material (pictures only, verbal paraphrases of the pictures, the latent content of the cartoons, or the combination of paraphrases and latent contents). The strongest effects were obtained when the originally presented cartoons were tested on their latent (deep semantic) contents. Recognition hypermnesia for part-forms or transforms of earlier presented stimuli has potentially wide-ranging implications since real-world recognition--of faces, texts, visual scenes--usually involves recognising stimuli that are variants, not exact copies, of the originally encountered materials. PMID:18608979

  10. Sleep Enhances Explicit Recollection in Recognition Memory

    ERIC Educational Resources Information Center

    Drosopoulos, Spyridon; Wagner, Ullrich; Born, Jan

    2005-01-01

    Recognition memory is considered to be supported by two different memory processes, i.e., the explicit recollection of information about a previous event and an implicit process of recognition based on a contextual sense of familiarity. Both types of memory supposedly rely on distinct memory systems. Sleep is known to enhance the consolidation of…

  11. Automatic Intention Recognition in Conversation Processing

    ERIC Educational Resources Information Center

    Holtgraves, Thomas

    2008-01-01

    A fundamental assumption of many theories of conversation is that comprehension of a speaker's utterance involves recognition of the speaker's intention in producing that remark. However, the nature of intention recognition is not clear. One approach is to conceptualize a speaker's intention in terms of speech acts [Searle, J. (1969). "Speech…

  12. Rapid Naming Speed and Chinese Character Recognition

    ERIC Educational Resources Information Center

    Liao, Chen-Huei; Georgiou, George K.; Parrila, Rauno

    2008-01-01

    We examined the relationship between rapid naming speed (RAN) and Chinese character recognition accuracy and fluency. Sixty-three grade 2 and 54 grade 4 Taiwanese children were administered four RAN tasks (colors, digits, Zhu-Yin-Fu-Hao, characters), and two character recognition tasks. RAN tasks accounted for more reading variance in grade 4 than…

  13. Adult Word Recognition and Visual Sequential Memory

    ERIC Educational Resources Information Center

    Holmes, V. M.

    2012-01-01

    Two experiments were conducted investigating the role of visual sequential memory skill in the word recognition efficiency of undergraduate university students. Word recognition was assessed in a lexical decision task using regularly and strangely spelt words, and nonwords that were either standard orthographically legal strings or items made from…

  14. Developmental, Crosslinguistic Perspectives on Visual Word Recognition

    ERIC Educational Resources Information Center

    Simpson, Greg B.; Kang, Hyewon

    2006-01-01

    In this paper, we argue that a complete understanding of language processing, in this case word-recognition processes, requires consideration both of multiple languages and of developmental processes. To illustrate these goals, we will summarize a 10-year research program exploring word-recognition processes in Korean adults and children. We…

  15. Syllable Transposition Effects in Korean Word Recognition

    ERIC Educational Resources Information Center

    Lee, Chang H.; Kwon, Youan; Kim, Kyungil; Rastle, Kathleen

    2015-01-01

    Research on the impact of letter transpositions in visual word recognition has yielded important clues about the nature of orthographic representations. This study investigated the impact of syllable transpositions on the recognition of Korean multisyllabic words. Results showed that rejection latencies in visual lexical decision for…

  16. The Commission on Magnet® Recognition.

    PubMed

    Moran, Janice W

    2016-09-01

    The American Nurses Credentialing Center (ANCC) Commission on Magnet® Recognition is a voluntary governing body that oversees the Magnet Recognition Program®. Commission members are appointed by the ANCC Board of Directors and are expert representatives from various sectors of the nursing community. In addition, 1 commission member represents public consumers. PMID:27556648

  17. Neural mechanisms for voice recognition.

    PubMed

    Andics, Attila; McQueen, James M; Petersson, Karl Magnus; Gál, Viktor; Rudas, Gábor; Vidnyánszky, Zoltán

    2010-10-01

    We investigated neural mechanisms that support voice recognition in a training paradigm with fMRI. The same listeners were trained on different weeks to categorize the mid-regions of voice-morph continua as an individual's voice. Stimuli implicitly defined a voice-acoustics space, and training explicitly defined a voice-identity space. The pre-defined centre of the voice category was shifted from the acoustic centre each week in opposite directions, so the same stimuli had different training histories on different tests. Cortical sensitivity to voice similarity appeared over different time-scales and at different representational stages. First, there were short-term adaptation effects: increasing acoustic similarity to the directly preceding stimulus led to haemodynamic response reduction in the middle/posterior STS and in right ventrolateral prefrontal regions. Second, there were longer-term effects: response reduction was found in the orbital/insular cortex for stimuli that were most versus least similar to the acoustic mean of all preceding stimuli, and, in the anterior temporal pole, the deep posterior STS and the amygdala, for stimuli that were most versus least similar to the trained voice-identity category mean. These findings are interpreted as effects of neural sharpening of long-term stored typical acoustic and category-internal values. The analyses also reveal anatomically separable voice representations: one in a voice-acoustics space and one in a voice-identity space. Voice-identity representations flexibly followed the trained identity shift, and listeners with a greater identity effect were more accurate at recognizing familiar voices. Voice recognition is thus supported by neural voice spaces that are organized around flexible 'mean voice' representations. PMID:20553895

  18. Cortical dynamics of word recognition.

    PubMed

    Mainy, Nelly; Jung, Julien; Baciu, Monica; Kahane, Philippe; Schoendorff, Benjamin; Minotti, Lorella; Hoffmann, Dominique; Bertrand, Olivier; Lachaux, Jean-Philippe

    2008-11-01

    While functional neuroimaging studies have helped elucidate major regions implicated in word recognition, much less is known about the dynamics of the associated activations or the actual neural processes of their functional network. We used intracerebral electroencephalography recordings in 10 patients with epilepsy to directly measure neural activity in the temporal and frontal lobes during written words' recognition, predominantly in the left hemisphere. The patients were presented visually with consonant strings, pseudo-words, and words and performed a hierarchical paradigm contrasting semantic processes (living vs. nonliving word categorization task), phonological processes (rhyme decision task on pseudo-words), and visual processes (visual analysis of consonant strings). Stimuli triggered a cascade of modulations in the gamma-band (>40 Hz) with reproducible timing and task-sensitivity throughout the functional reading network: the earliest gamma-band activations were observed for all stimuli in the mesial basal temporal lobe at 150 ms, reaching the word form area in the mid fusiform gyrus at 200 ms, evidencing a superiority effect for word-like stimuli. Peaks of gamma-band activations were then observed for word-like stimuli after 400 ms in the anterior and middle portion of the superior temporal gyrus (BA 38 and BA 22 respectively), in the pars triangularis of Broca's area for the semantic task (BAs 45 and 47), and in the pars opercularis for the phonological task (BA 44). Concurrently, we observed a two-pronged effect in the prefrontal cortex (BAs 9 and 46), with nonspecific sustained dorsal activation related to sustained attention and, more ventrally, a strong reflex deactivation around 500 ms, possibly due to semantic working memory reset. PMID:17712785

  19. Modal-Power-Based Haptic Motion Recognition

    NASA Astrophysics Data System (ADS)

    Kasahara, Yusuke; Shimono, Tomoyuki; Kuwahara, Hiroaki; Sato, Masataka; Ohnishi, Kouhei

    Motion recognition based on sensory information is important for providing assistance to human using robots. Several studies have been carried out on motion recognition based on image information. However, in the motion of humans contact with an object can not be evaluated precisely by image-based recognition. This is because the considering force information is very important for describing contact motion. In this paper, a modal-power-based haptic motion recognition is proposed; modal power is considered to reveal information on both position and force. Modal power is considered to be one of the defining features of human motion. A motion recognition algorithm based on linear discriminant analysis is proposed to distinguish between similar motions. Haptic information is extracted using a bilateral master-slave system. Then, the observed motion is decomposed in terms of primitive functions in a modal space. The experimental results show the effectiveness of the proposed method.

  20. Review of chart recognition in document images

    NASA Astrophysics Data System (ADS)

    Liu, Yan; Lu, Xiaoqing; Qin, Yeyang; Tang, Zhi; Xu, Jianbo

    2013-01-01

    As an effective information transmitting way, chart is widely used to represent scientific statistics datum in books, research papers, newspapers etc. Though textual information is still the major source of data, there has been an increasing trend of introducing graphs, pictures, and figures into the information pool. Text recognition techniques for documents have been accomplished using optical character recognition (OCR) software. Chart recognition techniques as a necessary supplement of OCR for document images are still an unsolved problem due to the great subjectiveness and variety of charts styles. This paper reviews the development process of chart recognition techniques in the past decades and presents the focuses of current researches. The whole process of chart recognition is presented systematically, which mainly includes three parts: chart segmentation, chart classification, and chart Interpretation. In each part, the latest research work is introduced. In the last, the paper concludes with a summary and promising future research direction.

  1. Articulation effects in melody recognition memory.

    PubMed

    Wee Hun Lim, Stephen; Goh, Winston D

    2013-09-01

    Various surface features-timbre, tempo, and pitch-influence melody recognition memory, but articulation format effects, if any, remain unknown. For the first time, these effects were examined. In Experiment 1, melodies that remained in the same, or appeared in a different but similar, articulation format from study to test were recognized better than were melodies that were presented in a distinct format at test. A similar articulation format adequately induced matching processes to enhance recognition. Experiment 2 revealed that melodies rated as perceptually dissimilar on the basis of the location of the articulation mismatch did not impair recognition performance, suggesting an important boundary condition for articulation format effects on memory recognition-the matching of the memory trace and recognition probe may depend more on the overall proportion, rather than the temporal location, of the mismatch. The present findings are discussed in terms of a global matching advantage hypothesis. PMID:23410265

  2. Practical automatic Arabic license plate recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Since 1970's, the need of an automatic license plate recognition system, sometimes referred as Automatic License Plate Recognition system, has been increasing. A license plate recognition system is an automatic system that is able to recognize a license plate number, extracted from image sensors. In specific, Automatic License Plate Recognition systems are being used in conjunction with various transportation systems in application areas such as law enforcement (e.g. speed limit enforcement) and commercial usages such as parking enforcement and automatic toll payment private and public entrances, border control, theft and vandalism control. Vehicle license plate recognition has been intensively studied in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is different for each country. [License plate detection using cluster run length smoothing algorithm ].Generally, an automatic license plate localization and recognition system is made up of three modules; license plate localization, character segmentation and optical character recognition modules. This paper presents an Arabic license plate recognition system that is insensitive to character size, font, shape and orientation with extremely high accuracy rate. The proposed system is based on a combination of enhancement, license plate localization, morphological processing, and feature vector extraction using the Haar transform. The performance of the system is fast due to classification of alphabet and numerals based on the license plate organization. Experimental results for license plates of two different Arab countries show an average of 99 % successful license plate localization and recognition in a total of more than 20 different images captured from a complex outdoor environment. The results run times takes less time compared to conventional and many states of art methods.

  3. Recognition of a signal peptide by the signal recognition particle

    PubMed Central

    Janda, Claudia Y.; Li, Jade; Oubridge, Chris; Hernández, Helena; Robinson, Carol V.; Nagai, Kiyoshi

    2010-01-01

    Targeting of proteins to appropriate sub-cellular compartments is a crucial process in all living cells. Secretory and membrane proteins usually contain an N-terminal signal peptide, which is recognised by the signal recognition particle (SRP) when nascent polypeptide chains emerge from the ribosome. The SRP-ribosome nascent chain complex is then targeted through its GTP-dependent interaction with SRP-receptor to the protein-conducting channel on endoplasmic reticulum membrane in eukaryotes or plasma membrane in bacteria. A universally conserved component of SRP1, 2, SRP54 or its bacterial homolog, fifty-four homolog (Ffh), binds the signal peptides which have a highly divergent sequence divisible into a positively charged n-region, an h-region commonly containing 8-20 hydrophobic residues and a polar c-region 3-5. No structure has been reported that exemplified SRP54 binding of any signal sequence. We have produced a fusion protein between Sulfolobus solfataricus SRP54 and a signal peptide connected via a flexible linker. This fusion protein oligomerises in solution, through interaction between the SRP54 and signal peptide moieties belonging to different chains, and it is functional, able to bind SRP RNA and SRP-receptor FtsY. Here we present the crystal structure at 3.5 Å resolution of an SRP54-signal peptide complex in the dimer, which reveals how a signal sequence is recognised by SRP54. PMID:20364120

  4. Apply lightweight recognition algorithms in optical music recognition

    NASA Astrophysics Data System (ADS)

    Pham, Viet-Khoi; Nguyen, Hai-Dang; Nguyen-Khac, Tung-Anh; Tran, Minh-Triet

    2015-02-01

    The problems of digitalization and transformation of musical scores into machine-readable format are necessary to be solved since they help people to enjoy music, to learn music, to conserve music sheets, and even to assist music composers. However, the results of existing methods still require improvements for higher accuracy. Therefore, the authors propose lightweight algorithms for Optical Music Recognition to help people to recognize and automatically play musical scores. In our proposal, after removing staff lines and extracting symbols, each music symbol is represented as a grid of identical M ∗ N cells, and the features are extracted and classified with multiple lightweight SVM classifiers. Through experiments, the authors find that the size of 10 ∗ 12 cells yields the highest precision value. Experimental results on the dataset consisting of 4929 music symbols taken from 18 modern music sheets in the Synthetic Score Database show that our proposed method is able to classify printed musical scores with accuracy up to 99.56%.

  5. Window size impact in human activity recognition.

    PubMed

    Banos, Oresti; Galvez, Juan-Manuel; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2014-01-01

    Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1-2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities. PMID:24721766

  6. The coevolution of recognition and social behavior

    PubMed Central

    Smead, Rory; Forber, Patrick

    2016-01-01

    Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation. PMID:27225673

  7. Window Size Impact in Human Activity Recognition

    PubMed Central

    Banos, Oresti; Galvez, Juan-Manuel; Damas, Miguel; Pomares, Hector; Rojas, Ignacio

    2014-01-01

    Signal segmentation is a crucial stage in the activity recognition process; however, this has been rarely and vaguely characterized so far. Windowing approaches are normally used for segmentation, but no clear consensus exists on which window size should be preferably employed. In fact, most designs normally rely on figures used in previous works, but with no strict studies that support them. Intuitively, decreasing the window size allows for a faster activity detection, as well as reduced resources and energy needs. On the contrary, large data windows are normally considered for the recognition of complex activities. In this work, we present an extensive study to fairly characterize the windowing procedure, to determine its impact within the activity recognition process and to help clarify some of the habitual assumptions made during the recognition system design. To that end, some of the most widely used activity recognition procedures are evaluated for a wide range of window sizes and activities. From the evaluation, the interval 1–2 s proves to provide the best trade-off between recognition speed and accuracy. The study, specifically intended for on-body activity recognition systems, further provides designers with a set of guidelines devised to facilitate the system definition and configuration according to the particular application requirements and target activities. PMID:24721766

  8. The coevolution of recognition and social behavior.

    PubMed

    Smead, Rory; Forber, Patrick

    2016-01-01

    Recognition of behavioral types can facilitate the evolution of cooperation by enabling altruistic behavior to be directed at other cooperators and withheld from defectors. While much is known about the tendency for recognition to promote cooperation, relatively little is known about whether such a capacity can coevolve with the social behavior it supports. Here we use evolutionary game theory and multi-population dynamics to model the coevolution of social behavior and recognition. We show that conditional harming behavior enables the evolution and stability of social recognition, whereas conditional helping leads to a deterioration of recognition ability. Expanding the model to include a complex game where both helping and harming interactions are possible, we find that conditional harming behavior can stabilize recognition, and thereby lead to the evolution of conditional helping. Our model identifies a novel hypothesis for the evolution of cooperation: conditional harm may have coevolved with recognition first, thereby helping to establish the mechanisms necessary for the evolution of cooperation. PMID:27225673

  9. Textual emotion recognition for enhancing enterprise computing

    NASA Astrophysics Data System (ADS)

    Quan, Changqin; Ren, Fuji

    2016-05-01

    The growing interest in affective computing (AC) brings a lot of valuable research topics that can meet different application demands in enterprise systems. The present study explores a sub area of AC techniques - textual emotion recognition for enhancing enterprise computing. Multi-label emotion recognition in text is able to provide a more comprehensive understanding of emotions than single label emotion recognition. A representation of 'emotion state in text' is proposed to encompass the multidimensional emotions in text. It ensures the description in a formal way of the configurations of basic emotions as well as of the relations between them. Our method allows recognition of the emotions for the words bear indirect emotions, emotion ambiguity and multiple emotions. We further investigate the effect of word order for emotional expression by comparing the performances of bag-of-words model and sequence model for multi-label sentence emotion recognition. The experiments show that the classification results under sequence model are better than under bag-of-words model. And homogeneous Markov model showed promising results of multi-label sentence emotion recognition. This emotion recognition system is able to provide a convenient way to acquire valuable emotion information and to improve enterprise competitive ability in many aspects.

  10. Recognition in a social symbiosis: chemical phenotypes and nestmate recognition behaviors of neotropical parabiotic ants.

    PubMed

    Emery, Virginia J; Tsutsui, Neil D

    2013-01-01

    Social organisms rank among the most abundant and ecologically dominant species on Earth, in part due to exclusive recognition systems that allow cooperators to be distinguished from exploiters. Exploiters, such as social parasites, manipulate their hosts' recognition systems, whereas cooperators are expected to minimize interference with their partner's recognition abilities. Despite our wealth of knowledge about recognition in single-species social nests, less is known of the recognition systems in multi-species nests, particularly involving cooperators. One uncommon type of nesting symbiosis, called parabiosis, involves two species of ants sharing a nest and foraging trails in ostensible cooperation. Here, we investigated recognition cues (cuticular hydrocarbons) and recognition behaviors in the parabiotic mixed-species ant nests of Camponotus femoratus and Crematogaster levior in North-Eastern Amazonia. We found two sympatric, cryptic Cr. levior chemotypes in the population, with one type in each parabiotic colony. Although they share a nest, very few hydrocarbons were shared between Ca. femoratus and either Cr. levior chemotype. The Ca. femoratus hydrocarbons were also unusually long-chained branched alkenes and dienes, compounds not commonly found amongst ants. Despite minimal overlap in hydrocarbon profile, there was evidence of potential interspecific nestmate recognition -Cr. levior ants were more aggressive toward Ca. femoratus non-nestmates than Ca. femoratus nestmates. In contrast to the prediction that sharing a nest could weaken conspecific recognition, each parabiotic species also maintains its own aggressive recognition behaviors to exclude conspecific non-nestmates. This suggests that, despite cohabitation, parabiotic ants maintain their own species-specific colony odors and recognition mechanisms. It is possible that such social symbioses are enabled by the two species each using their own separate recognition cues, and that interspecific nestmate

  11. Maritime vessel recognition in degraded satellite imagery

    NASA Astrophysics Data System (ADS)

    Rainey, Katie; Parameswaran, Shibin; Harguess, Josh

    2014-06-01

    When object recognition algorithms are put to practice on real-world data, they face hurdles not always present in experimental situations. Imagery fed into recognition systems is often degraded by noise, occlusions, or other factors, and a successful recognition algorithm must be accurate on such data. This work investigates the impact of data degradations on an algorithm for the task of ship classification in satellite imagery by imposing such degradation factors on both training and testing data. The results of these experiments provide lessons for the development of real-world applications for classification algorithms.

  12. Place recognition using batlike sonar

    PubMed Central

    Vanderelst, Dieter; Steckel, Jan; Boen, Andre; Peremans, Herbert; Holderied, Marc W

    2016-01-01

    Echolocating bats have excellent spatial memory and are able to navigate to salient locations using bio-sonar. Navigating and route-following require animals to recognize places. Currently, it is mostly unknown how bats recognize places using echolocation. In this paper, we propose template based place recognition might underlie sonar-based navigation in bats. Under this hypothesis, bats recognize places by remembering their echo signature - rather than their 3D layout. Using a large body of ensonification data collected in three different habitats, we test the viability of this hypothesis assessing two critical properties of the proposed echo signatures: (1) they can be uniquely classified and (2) they vary continuously across space. Based on the results presented, we conclude that the proposed echo signatures satisfy both criteria. We discuss how these two properties of the echo signatures can support navigation and building a cognitive map. DOI: http://dx.doi.org/10.7554/eLife.14188.001 PMID:27481189

  13. Learning curve of speech recognition.

    PubMed

    Kauppinen, Tomi A; Kaipio, Johanna; Koivikko, Mika P

    2013-12-01

    Speech recognition (SR) speeds patient care processes by reducing report turnaround times. However, concerns have emerged about prolonged training and an added secretarial burden for radiologists. We assessed how much proofing radiologists who have years of experience with SR and radiologists new to SR must perform, and estimated how quickly the new users become as skilled as the experienced users. We studied SR log entries for 0.25 million reports from 154 radiologists and after careful exclusions, defined a group of 11 experienced radiologists and 71 radiologists new to SR (24,833 and 122,093 reports, respectively). Data were analyzed for sound file and report lengths, character-based error rates, and words unknown to the SR's dictionary. Experienced radiologists corrected 6 characters for each report and for new users, 11. Some users presented a very unfavorable learning curve, with error rates not declining as expected. New users' reports were longer, and data for the experienced users indicates that their reports, initially equally lengthy, shortened over a period of several years. For most radiologists, only minor corrections of dictated reports were necessary. While new users adopted SR quickly, with a subset outperforming experienced users from the start, identification of users struggling with SR will help facilitate troubleshooting and support. PMID:23779151

  14. Distributed nestmate recognition in ants

    PubMed Central

    Esponda, Fernando; Gordon, Deborah M.

    2015-01-01

    We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response. PMID:25833853

  15. Recurrent Processing during Object Recognition

    PubMed Central

    O’Reilly, Randall C.; Wyatte, Dean; Herd, Seth; Mingus, Brian; Jilk, David J.

    2013-01-01

    How does the brain learn to recognize objects visually, and perform this difficult feat robustly in the face of many sources of ambiguity and variability? We present a computational model based on the biology of the relevant visual pathways that learns to reliably recognize 100 different object categories in the face of naturally occurring variability in location, rotation, size, and lighting. The model exhibits robustness to highly ambiguous, partially occluded inputs. Both the unified, biologically plausible learning mechanism and the robustness to occlusion derive from the role that recurrent connectivity and recurrent processing mechanisms play in the model. Furthermore, this interaction of recurrent connectivity and learning predicts that high-level visual representations should be shaped by error signals from nearby, associated brain areas over the course of visual learning. Consistent with this prediction, we show how semantic knowledge about object categories changes the nature of their learned visual representations, as well as how this representational shift supports the mapping between perceptual and conceptual knowledge. Altogether, these findings support the potential importance of ongoing recurrent processing throughout the brain’s visual system and suggest ways in which object recognition can be understood in terms of interactions within and between processes over time. PMID:23554596

  16. Aircraft recognition and pose estimation

    NASA Astrophysics Data System (ADS)

    Hmam, Hatem; Kim, Jijoong

    2000-05-01

    This work presents a geometry based vision system for aircraft recognition and pose estimation using single images. Pose estimation improves the tracking performance of guided weapons with imaging seekers, and is useful in estimating target manoeuvres and aim-point selection required in the terminal phase of missile engagements. After edge detection and straight-line extraction, a hierarchy of geometric reasoning algorithms is applied to form line clusters (or groupings) for image interpretation. Assuming a scaled orthographic projection and coplanar wings, lateral symmetry inherent in the airframe provides additional constraints to further reject spurious line clusters. Clusters that accidentally pass all previous tests are checked against the original image and are discarded. Valid line clusters are then used to deduce aircraft viewing angles. By observing that the leading edges of wings of a number of aircraft of interest are within 45 to 65 degrees from the symmetry axis, a bounded range of aircraft viewing angles can be found. This generic property offers the advantage of not requiring the storage of complete aircraft models viewed from all aspects, and can handle aircraft with flexible wings (e.g. F111). Several aircraft images associated with various spectral bands (i.e. visible and infra-red) are finally used to evaluate the system's performance.

  17. Combinatorial methods for gene recognition

    SciTech Connect

    Pevzner, P.A.

    1997-10-29

    The major result of the project is the development of a new approach to gene recognition called spliced alignment algorithm. They have developed an algorithm and implemented a software tool (for both IBM PC and UNIX platforms) which explores all possible exon assemblies in polynomial time and finds the multi-exon structure with the best fit to a related protein. Unlike other existing methods, the algorithm successfully performs exons assemblies even in the case of short exons or exons with unusual codon usage; they also report correct assemblies for the genes with more than 10 exons provided a homologous protein is already known. On a test sample of human genes with known mammalian relatives the average overlap between the predicted and the actual genes was 99%, which is remarkably well as compared to other existing methods. At that, the algorithm absolute correctly reconstructed 87% of genes. The rare discrepancies between the predicted and real axon-intron structures were restricted either to extremely short initial or terminal exons or proved to be results of alternative splicing. Moreover, the algorithm performs reasonably well with non-vertebrate and even prokaryote targets. The spliced alignment software PROCRUSTES has been in extensive use by the academic community since its announcement in August, 1996 via the WWW server (www-hto.usc.edu/software/procrustes) and by biotech companies via the in-house UNIX version.

  18. Distributed nestmate recognition in ants.

    PubMed

    Esponda, Fernando; Gordon, Deborah M

    2015-05-01

    We propose a distributed model of nestmate recognition, analogous to the one used by the vertebrate immune system, in which colony response results from the diverse reactions of many ants. The model describes how individual behaviour produces colony response to non-nestmates. No single ant knows the odour identity of the colony. Instead, colony identity is defined collectively by all the ants in the colony. Each ant responds to the odour of other ants by reference to its own unique decision boundary, which is a result of its experience of encounters with other ants. Each ant thus recognizes a particular set of chemical profiles as being those of non-nestmates. This model predicts, as experimental results have shown, that the outcome of behavioural assays is likely to be variable, that it depends on the number of ants tested, that response to non-nestmates changes over time and that it changes in response to the experience of individual ants. A distributed system allows a colony to identify non-nestmates without requiring that all individuals have the same complete information and helps to facilitate the tracking of changes in cuticular hydrocarbon profiles, because only a subset of ants must respond to provide an adequate response. PMID:25833853

  19. Temporal regulation of kin recognition maintains recognition-cue diversity and suppresses cheating

    PubMed Central

    Ho, Hsing-I; Shaulsky, Gad

    2015-01-01

    Kin recognition, the ability to distinguish kin from non-kin, can facilitate cooperation between relatives. Evolutionary theory predicts that polymorphism in recognition cues, which is essential for effective recognition, would be unstable. Individuals carrying rare recognition cues would benefit less from social interactions than individuals with common cues, leading to loss of the genetic-cue diversity. We test this evolutionary hypothesis in Dictyostelium discoideum, which forms multicellular fruiting bodies by aggregation and utilizes two polymorphic membrane proteins to facilitate preferential cooperation. Surprisingly, we find that rare recognition variants are tolerated and maintain their frequencies among incompatible majority during development. Although the rare variants are initially excluded from the aggregates, they subsequently rejoin the aggregate and produce spores. Social cheating is also refrained in late development, thus limiting the cost of chimerism. Our results suggest a potential mechanism to sustain the evolutionary stability of kin-recognition genes and to suppress cheating. PMID:26018043

  20. Temporal regulation of kin recognition maintains recognition-cue diversity and suppresses cheating.

    PubMed

    Ho, Hsing-I; Shaulsky, Gad

    2015-01-01

    Kin recognition, the ability to distinguish kin from non-kin, can facilitate cooperation between relatives. Evolutionary theory predicts that polymorphism in recognition cues, which is essential for effective recognition, would be unstable. Individuals carrying rare recognition cues would benefit less from social interactions than individuals with common cues, leading to loss of the genetic-cue diversity. We test this evolutionary hypothesis in Dictyostelium discoideum, which forms multicellular fruiting bodies by aggregation and utilizes two polymorphic membrane proteins to facilitate preferential cooperation. Surprisingly, we find that rare recognition variants are tolerated and maintain their frequencies among incompatible majority during development. Although the rare variants are initially excluded from the aggregates, they subsequently rejoin the aggregate and produce spores. Social cheating is also refrained in late development, thus limiting the cost of chimerism. Our results suggest a potential mechanism to sustain the evolutionary stability of kin-recognition genes and to suppress cheating. PMID:26018043

  1. Support vector machine for automatic pain recognition

    NASA Astrophysics Data System (ADS)

    Monwar, Md Maruf; Rezaei, Siamak

    2009-02-01

    Facial expressions are a key index of emotion and the interpretation of such expressions of emotion is critical to everyday social functioning. In this paper, we present an efficient video analysis technique for recognition of a specific expression, pain, from human faces. We employ an automatic face detector which detects face from the stored video frame using skin color modeling technique. For pain recognition, location and shape features of the detected faces are computed. These features are then used as inputs to a support vector machine (SVM) for classification. We compare the results with neural network based and eigenimage based automatic pain recognition systems. The experiment results indicate that using support vector machine as classifier can certainly improve the performance of automatic pain recognition system.

  2. Innate predator recognition in giant pandas.

    PubMed

    Du, Yiping; Huang, Yan; Zhang, Hemin; Li, Desheng; Yang, Bo; Wei, Ming; Zhou, Yingmin; Liu, Yang

    2012-02-01

    Innate predator recognition confers a survival advantage to prey animals. We investigate whether giant pandas exhibit innate predator recognition. We analyzed behavioral responses of 56 naive adult captive giant pandas (Ailuropoda melanoleuca), to urine from predators and non-predators and water control. Giant pandas performed more chemosensory investigation and displayed flehmen behaviors more frequently in response to predator urine compared to both non-predator urine and water control. Subjects also displayed certain defensive behaviors, as indicated by vigilance, and in certain cases, fleeing behaviors. Our results suggest that there is an innate component to predator recognition in captive giant pandas, although such recognition was only slight to moderate. These results have implications that may be applicable to the conservation and reintroduction of this endangered species. PMID:22303845

  3. Hybrid Speaker Recognition Using Universal Acoustic Model

    NASA Astrophysics Data System (ADS)

    Nishimura, Jun; Kuroda, Tadahiro

    We propose a novel speaker recognition approach using a speaker-independent universal acoustic model (UAM) for sensornet applications. In sensornet applications such as “Business Microscope”, interactions among knowledge workers in an organization can be visualized by sensing face-to-face communication using wearable sensor nodes. In conventional studies, speakers are detected by comparing energy of input speech signals among the nodes. However, there are often synchronization errors among the nodes which degrade the speaker recognition performance. By focusing on property of the speaker's acoustic channel, UAM can provide robustness against the synchronization error. The overall speaker recognition accuracy is improved by combining UAM with the energy-based approach. For 0.1s speech inputs and 4 subjects, speaker recognition accuracy of 94% is achieved at the synchronization error less than 100ms.

  4. Hand gesture recognition based on surface electromyography.

    PubMed

    Samadani, Ali-Akbar; Kulic, Dana

    2014-01-01

    Human hands are the most dexterous of human limbs and hand gestures play an important role in non-verbal communication. Underlying electromyograms associated with hand gestures provide a wealth of information based on which varying hand gestures can be recognized. This paper develops an inter-individual hand gesture recognition model based on Hidden Markov models that receives surface electromyography (sEMG) signals as inputs and predicts a corresponding hand gesture. The developed recognition model is tested with a dataset of 10 various hand gestures performed by 25 subjects in a leave-one-subject-out cross validation and an inter-individual recognition rate of 79% was achieved. The promising recognition rate demonstrates the efficacy of the proposed approach for discriminating between gesture-specific sEMG signals and could inform the design of sEMG-controlled prostheses and assistive devices. PMID:25570917

  5. Improved MFCC algorithm in speaker recognition system

    NASA Astrophysics Data System (ADS)

    Shi, Yibo; Wang, Li

    2011-10-01

    In speaker recognition systems, one of the key feature parameters is MFCC, which can be used for speaker recognition. So, how to extract MFCC parameter in speech signals more exactly and efficiently, decides the performance of the system. Theoretically, MFCC parameters are used to describe the spectrum envelope of the vocal tract characteristics and often ignore the impacts of fundamental frequency. But in practice, MFCC can be influenced by fundamental frequency which can cause palpable performance reduction. So, smoothing MFCC (SMFCC), which based on smoothing short-term spectral amplitude envelope, has been proposed to improve MFCC algorithm. Experimental results show that improved MFCC parameters---SMFCC can degrade the bad influences of fundamental frequency effectively and upgrade the performances of speaker recognition system. Especially for female speakers, who have higher fundamental frequency, the recognition rate improves more significantly.

  6. Visual cluster analysis and pattern recognition methods

    DOEpatents

    Osbourn, Gordon Cecil; Martinez, Rubel Francisco

    2001-01-01

    A method of clustering using a novel template to define a region of influence. Using neighboring approximation methods, computation times can be significantly reduced. The template and method are applicable and improve pattern recognition techniques.

  7. Image-based automatic recognition of larvae

    NASA Astrophysics Data System (ADS)

    Sang, Ru; Yu, Guiying; Fan, Weijun; Guo, Tiantai

    2010-08-01

    As the main objects, imagoes have been researched in quarantine pest recognition in these days. However, pests in their larval stage are latent, and the larvae spread abroad much easily with the circulation of agricultural and forest products. It is presented in this paper that, as the new research objects, larvae are recognized by means of machine vision, image processing and pattern recognition. More visional information is reserved and the recognition rate is improved as color image segmentation is applied to images of larvae. Along with the characteristics of affine invariance, perspective invariance and brightness invariance, scale invariant feature transform (SIFT) is adopted for the feature extraction. The neural network algorithm is utilized for pattern recognition, and the automatic identification of larvae images is successfully achieved with satisfactory results.

  8. Speech therapy and voice recognition instrument

    NASA Technical Reports Server (NTRS)

    Cohen, J.; Babcock, M. L.

    1972-01-01

    Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

  9. History of Maternal Recognition of Pregnancy.

    PubMed

    Bazer, Fuller W

    2015-01-01

    The mechanism for signaling pregnancy recognition is highly variable among species, and the signaling molecule itself varies between estrogens in pigs to chorionic gonadotrophin in primates. This chapter provides insight into the menstrual cycle of women and estrous cycles of rodents, dog, cat, pigs, sheep, rabbits, and marsupials, as well as the hormones required for pregnancy recognition. Pregnancy recognition involves specific hormones such as prolactin in rodents or interferons in ruminants and estrogens in pigs that in their own way ensure the maintenance of the corpus luteum and its secretion of progesterone which is the hormone of pregnancy. However, these pregnancy recognition signals may also modify gene expression in a cell-specific and temporal manner to ensure the growth and development of the conceptus. This chapter provides some historical aspects of the development of understanding of mechanisms for the establishment and maintenance of pregnancy in several species of mammals. PMID:26450492

  10. Gabor wavelet associative memory for face recognition.

    PubMed

    Zhang, Haihong; Zhang, Bailing; Huang, Weimin; Tian, Qi

    2005-01-01

    This letter describes a high-performance face recognition system by combining two recently proposed neural network models, namely Gabor wavelet network (GWN) and kernel associative memory (KAM), into a unified structure called Gabor wavelet associative memory (GWAM). GWAM has superior representation capability inherited from GWN and consequently demonstrates a much better recognition performance than KAM. Extensive experiments have been conducted to evaluate a GWAM-based recognition scheme using three popular face databases, i.e., FERET database, Olivetti-Oracle Research Lab (ORL) database and AR face database. The experimental results consistently show our scheme's superiority and demonstrate its very high-performance comparing favorably to some recent face recognition methods, achieving 99.3% and 100% accuracy, respectively, on the former two databases, exhibiting very robust performance on the last database against varying illumination conditions. PMID:15732406

  11. An Efficient Gait Recognition with Backpack Removal

    NASA Astrophysics Data System (ADS)

    Lee, Heesung; Hong, Sungjun; Kim, Euntai

    2009-12-01

    Gait-based human identification is a paradigm to recognize individuals using visual cues that characterize their walking motion. An important requirement for successful gait recognition is robustness to variations including different lighting conditions, poses, and walking speed. Deformation of the gait silhouette caused by objects carried by subjects also has a significant effect on the performance of gait recognition systems; a backpack is the most common of these objects. This paper proposes methods for eliminating the effect of a carried backpack for efficient gait recognition. We apply simple, recursive principal component analysis (PCA) reconstructions and error compensation to remove the backpack from the gait representation and then conduct gait recognition. Experiments performed with the CASIA database illustrate the performance of the proposed algorithm.

  12. Nucleic acid recognition by tandem helical repeats.

    PubMed

    Rubinson, Emily H; Eichman, Brandt F

    2012-02-01

    Protein domains constructed from tandem α-helical repeats have until recently been primarily associated with protein scaffolds or RNA recognition. Recent crystal structures of human mitochondrial termination factor MTERF1 and Bacillus cereus alkylpurine DNA glycosylase AlkD bound to DNA revealed two new superhelical tandem repeat architectures capable of wrapping around the double helix in unique ways. Unlike DNA sequence recognition motifs that rely mainly on major groove read-out, MTERF and ALK motifs locate target sequences and aberrant nucleotides within DNA by resculpting the double-helix through extensive backbone contacts. Comparisons between MTERF and ALK repeats, together with recent advances in ssRNA recognition by Pumilio/FBF (PUF) domains, provide new insights into the fundamental principles of protein-nucleic acid recognition. PMID:22154606

  13. Antigen Recognition By Variable Lymphocyte Receptors

    SciTech Connect

    Han, B.W.; Herrin, B.R.; Cooper, M.D.; Wilson, I.A.

    2009-05-18

    Variable lymphocyte receptors (VLRs) rather than antibodies play the primary role in recognition of antigens in the adaptive immune system of jawless vertebrates. Combinatorial assembly of leucine-rich repeat (LRR) gene segments achieves the required repertoire for antigen recognition. We have determined a crystal structure for a VLR-antigen complex, VLR RBC36 in complex with the H-antigen trisaccharide from human blood type O erythrocytes, at 1.67 angstrom resolution. RBC36 binds the H-trisaccharide on the concave surface of the LRR modules of the solenoid structure where three key hydrophilic residues, multiple van der Waals interactions, and the highly variable insert of the carboxyl-terminal LRR module determine antigen recognition and specificity. The concave surface assembled from the most highly variable regions of the LRRs, along with diversity in the sequence and length of the highly variable insert, can account for the recognition of diverse antigens by VLRs.

  14. Description, Recognition and Analysis of Biological Images

    SciTech Connect

    Yu Donggang; Jin, Jesse S.; Luo Suhuai; Pham, Tuan D.; Lai Wei

    2010-01-25

    Description, recognition and analysis biological images plays an important role for human to describe and understand the related biological information. The color images are separated by color reduction. A new and efficient linearization algorithm is introduced based on some criteria of difference chain code. A series of critical points is got based on the linearized lines. The series of curvature angle, linearity, maximum linearity, convexity, concavity and bend angle of linearized lines are calculated from the starting line to the end line along all smoothed contours. The useful method can be used for shape description and recognition. The analysis, decision, classification of the biological images are based on the description of morphological structures, color information and prior knowledge, which are associated each other. The efficiency of the algorithms is described based on two applications. One application is the description, recognition and analysis of color flower images. Another one is related to the dynamic description, recognition and analysis of cell-cycle images.

  15. Door latching recognition apparatus and process

    DOEpatents

    Eakle, Jr., Robert F.

    2012-05-15

    An acoustic door latch detector is provided in which a sound recognition sensor is integrated into a door or door lock mechanism. The programmable sound recognition sensor can be trained to recognize the acoustic signature of the door and door lock mechanism being properly engaged and secured. The acoustic sensor will signal a first indicator indicating that proper closure was detected or sound an alarm condition if the proper acoustic signature is not detected within a predetermined time interval.

  16. Diversity in protein recognition by PTB domains.

    PubMed

    Forman-Kay, J D; Pawson, T

    1999-12-01

    Phosphotyrosine-binding (PTB) domains were originally identified as modular domains that recognize phosphorylated Asn-Pro-Xxx-p Tyr-containing proteins. Recent binding and structural studies of PTB domain complexes with target peptides have revealed a number of deviations from the previously described mode of interaction, with respect to both the sequences of possible targets and their structures within the complexes. This diversity of recognition by PTB domains extends and strengthens our general understanding of modular binding domain recognition. PMID:10607674

  17. Pattern recognition using linguistic fuzzy logic predictors

    NASA Astrophysics Data System (ADS)

    Habiballa, Hashim

    2016-06-01

    The problem of pattern recognition has been solved with numerous methods in the Artificial Intelligence field. We present an unconventional method based on Lingustic Fuzzy Logic Forecaster which is primarily used for the task of time series analysis and prediction through logical deduction wtih linguistic variables. This method should be used not only to the time series prediction itself, but also for recognition of patterns in a signal with seasonal component.

  18. Early recognition of chemical dependence.

    PubMed

    Maly, R C

    1993-03-01

    Chemical dependence is a leading cause of morbidity and death in the United States. At least 20% of patients seen by primary care physicians in both the outpatient and inpatient setting are chemically dependent. Up to 90% of these patients go undiagnosed by their primary physicians. Chemical dependence is defined as a chronic, progressive illness characterized by the repeated and persistent use of alcohol or drugs despite negative health, family, work, financial, or legal consequences. Primary care physicians are in an ideal position to detect chemical dependence at its earliest stages, when irreversible medical consequences and death are most likely preventable. Alcohol is the most common drug of abuse. Improving the rate of recognition of chemical dependence depends on being familiar with the constellation of physical, mental, and social indicators. Early medical manifestations of alcoholism common in the primary care setting include: gastric complaints, elevated blood pressure, palpitations, traumatic injuries, headaches, impotence, and gout. Early psychosocial manifestations common in both alcohol and drug dependence include anxiety, depression, insomnia, persistent relationship conflicts, work or school problems, and financial or legal problems. Particularly useful laboratory indicators of alcoholism include elevated levels of GGT and MCV, both displaying high specificity, with the GGT level being the most sensitive. Similarly specific laboratory tests for drug dependence are not available. Any patient presenting with any of the above medical, psychosocial, or laboratory manifestations should be screened for chemical dependence. The CAGE questionnaire for alcoholism, a four-question test, is particularly well suited to the primary care setting, where it can be administered in fewer than 60 seconds. The CAGE has demonstrated high sensitivity (in the 80% range) and specificity (approximately 85%) for alcoholism. Comparably convenient instruments do not yet exist

  19. Object recognition by artificial cortical maps.

    PubMed

    Plebe, Alessio; Domenella, Rosaria Grazia

    2007-09-01

    Object recognition is one of the most important functions of the human visual system, yet one of the least understood, this despite the fact that vision is certainly the most studied function of the brain. We understand relatively well how several processes in the cortical visual areas that support recognition capabilities take place, such as orientation discrimination and color constancy. This paper proposes a model of the development of object recognition capability, based on two main theoretical principles. The first is that recognition does not imply any sort of geometrical reconstruction, it is instead fully driven by the two dimensional view captured by the retina. The second assumption is that all the processing functions involved in recognition are not genetically determined or hardwired in neural circuits, but are the result of interactions between epigenetic influences and basic neural plasticity mechanisms. The model is organized in modules roughly related to the main visual biological areas, and is implemented mainly using the LISSOM architecture, a recent neural self-organizing map model that simulates the effects of intercortical lateral connections. This paper shows how recognition capabilities, similar to those found in brain ventral visual areas, can develop spontaneously by exposure to natural images in an artificial cortical model. PMID:17604954

  20. Color pattern recognition with CIELAB coordinates

    NASA Astrophysics Data System (ADS)

    Corbalan-Fuertes, Montserrat; Millan Garcia-Verela, Maria S.; Yzuel, Maria J.

    2002-01-01

    A color pattern recognition system must identify a target by its shape and color distribution. In real situations, however, the color information is affected by changes of the light source (e.g., from indoor illumination to outdoor daylight), often making recognition impossible. In this work, we propose a color pattern recognition technique with tolerance for illumination changes within the common sources of white light. This can be accomplished using the coordinates of the CIELAB system, luminance (L*), chroma (C*), and hue (h*) instead of the conventional RGB system. The proposal has some additional advantages: there is no need to store a matched filters base to analyze scenes captured under different light sources (one set of filters for each illuminant light source) and therefore the recognition process can be simplified; and in most cases, the contribution of only two channels (C* and h*) is enough to avoid false alarms in color pattern recognition. From the results, we show that the recognition system is improved when CIELAB coordinates are used.

  1. Face Recognition in Humans and Machines

    NASA Astrophysics Data System (ADS)

    O'Toole, Alice; Tistarelli, Massimo

    The study of human face recognition by psychologists and neuroscientists has run parallel to the development of automatic face recognition technologies by computer scientists and engineers. In both cases, there are analogous steps of data acquisition, image processing, and the formation of representations that can support the complex and diverse tasks we accomplish with faces. These processes can be understood and compared in the context of their neural and computational implementations. In this chapter, we present the essential elements of face recognition by humans and machines, taking a perspective that spans psychological, neural, and computational approaches. From the human side, we overview the methods and techniques used in the neurobiology of face recognition, the underlying neural architecture of the system, the role of visual attention, and the nature of the representations that emerges. From the computational side, we discuss face recognition technologies and the strategies they use to overcome challenges to robust operation over viewing parameters. Finally, we conclude the chapter with a look at some recent studies that compare human and machine performances at face recognition.

  2. Selecting and implementing a voice recognition system.

    PubMed

    Wheeler, S; Cassimus, G C

    1999-01-01

    A single radiology department serves the three separate organizations that comprise Emory Healthcare in Atlanta--three separate hospitals, the Emory Clinic and the Emory University School of Medicine. In 1996, the chairman of Emory Healthcare issued a mandate to the radiology department to decrease its report turnaround time, provide better service and increase customer satisfaction. The area where the greatest effect could be made without involving the transcription area was the "exam complete to dictate" piece of the reporting process. A committee investigating voice recognition systems established an essential criteria for potential vendors--to be able to download patient scheduling and demographic information from the existing RIS to the new system. Second, the system had to be flexible and straightforward for doctors to learn. It must have a word processing package for easy report correction and editing, and a microphone that would rewind and correct dictation before recognition took place. To keep capital costs low for the pilot, the committee opted for server recognition rather than purchase the expensive workstations necessary for real-time recognition. A switch was made later to real-time recognition. PACS and voice recognition have proven to be highly complementary. Most importantly, the new system has had a tremendous impact on turnaround time in the "dictate to final" phase. Once in the 30-hour range, 65 percent of the reports are now turned around in less than 15 minutes, 80 percent in less than 30 minutes, and 90 percent in less than an hour. PMID:10558032

  3. Oxytocin improves emotion recognition for older males.

    PubMed

    Campbell, Anna; Ruffman, Ted; Murray, Janice E; Glue, Paul

    2014-10-01

    Older adults (≥60 years) perform worse than young adults (18-30 years) when recognizing facial expressions of emotion. The hypothesized cause of these changes might be declines in neurotransmitters that could affect information processing within the brain. In the present study, we examined the neuropeptide oxytocin that functions to increase neurotransmission. Research suggests that oxytocin benefits the emotion recognition of less socially able individuals. Men tend to have lower levels of oxytocin and older men tend to have worse emotion recognition than older women; therefore, there is reason to think that older men will be particularly likely to benefit from oxytocin. We examined this idea using a double-blind design, testing 68 older and 68 young adults randomly allocated to receive oxytocin nasal spray (20 international units) or placebo. Forty-five minutes afterward they completed an emotion recognition task assessing labeling accuracy for angry, disgusted, fearful, happy, neutral, and sad faces. Older males receiving oxytocin showed improved emotion recognition relative to those taking placebo. No differences were found for older females or young adults. We hypothesize that oxytocin facilitates emotion recognition by improving neurotransmission in the group with the worst emotion recognition. PMID:24856057

  4. Multispectral Palmprint Recognition Using a Quaternion Matrix

    PubMed Central

    Xu, Xingpeng; Guo, Zhenhua; Song, Changjiang; Li, Yafeng

    2012-01-01

    Palmprints have been widely studied for biometric recognition for many years. Traditionally, a white light source is used for illumination. Recently, multispectral imaging has drawn attention because of its high recognition accuracy. Multispectral palmprint systems can provide more discriminant information under different illuminations in a short time, thus they can achieve better recognition accuracy. Previously, multispectral palmprint images were taken as a kind of multi-modal biometrics, and the fusion scheme on the image level or matching score level was used. However, some spectral information will be lost during image level or matching score level fusion. In this study, we propose a new method for multispectral images based on a quaternion model which could fully utilize the multispectral information. Firstly, multispectral palmprint images captured under red, green, blue and near-infrared (NIR) illuminations were represented by a quaternion matrix, then principal component analysis (PCA) and discrete wavelet transform (DWT) were applied respectively on the matrix to extract palmprint features. After that, Euclidean distance was used to measure the dissimilarity between different features. Finally, the sum of two distances and the nearest neighborhood classifier were employed for recognition decision. Experimental results showed that using the quaternion matrix can achieve a higher recognition rate. Given 3000 test samples from 500 palms, the recognition rate can be as high as 98.83%. PMID:22666049

  5. Physical environment virtualization for human activities recognition

    NASA Astrophysics Data System (ADS)

    Poshtkar, Azin; Elangovan, Vinayak; Shirkhodaie, Amir; Chan, Alex; Hu, Shuowen

    2015-05-01

    Human activity recognition research relies heavily on extensive datasets to verify and validate performance of activity recognition algorithms. However, obtaining real datasets are expensive and highly time consuming. A physics-based virtual simulation can accelerate the development of context based human activity recognition algorithms and techniques by generating relevant training and testing videos simulating diverse operational scenarios. In this paper, we discuss in detail the requisite capabilities of a virtual environment to aid as a test bed for evaluating and enhancing activity recognition algorithms. To demonstrate the numerous advantages of virtual environment development, a newly developed virtual environment simulation modeling (VESM) environment is presented here to generate calibrated multisource imagery datasets suitable for development and testing of recognition algorithms for context-based human activities. The VESM environment serves as a versatile test bed to generate a vast amount of realistic data for training and testing of sensor processing algorithms. To demonstrate the effectiveness of VESM environment, we present various simulated scenarios and processed results to infer proper semantic annotations from the high fidelity imagery data for human-vehicle activity recognition under different operational contexts.

  6. Robust coarticulatory modeling for continuous speech recognition

    NASA Astrophysics Data System (ADS)

    Schwartz, R.; Chow, Y. L.; Dunham, M. O.; Kimball, O.; Krasner, M.; Kubala, F.; Makhoul, J.; Price, P.; Roucos, S.

    1986-10-01

    The purpose of this project is to perform research into algorithms for the automatic recognition of individual sounds or phonemes in continuous speech. The algorithms developed should be appropriate for understanding large-vocabulary continuous speech input and are to be made available to the Strategic Computing Program for incorporation in a complete word recognition system. This report describes process to date in developing phonetic models that are appropriate for continuous speech recognition. In continuous speech, the acoustic realization of each phoneme depends heavily on the preceding and following phonemes: a process known as coarticulation. Thus, while there are relatively few phonemes in English (on the order of fifty or so), the number of possible different accoustic realizations is in the thousands. Therefore, to develop high-accuracy recognition algorithms, one may need to develop literally thousands of relatively distance phonetic models to represent the various phonetic context adequately. Developing a large number of models usually necessitates having a large amount of speech to provide reliable estimates of the model parameters. The major contributions of this work are the development of: (1) A simple but powerful formalism for modeling phonemes in context; (2) Robust training methods for the reliable estimation of model parameters by utilizing the available speech training data in a maximally effective way; and (3) Efficient search strategies for phonetic recognition while maintaining high recognition accuracy.

  7. Optical pattern recognition for missile guidance

    NASA Astrophysics Data System (ADS)

    Casasent, D.

    1982-11-01

    Progress on real-time spatial light modulators, image pattern recognition and optical signal processing for missile guidance is documented. A full description of our test and evaluation of the Soviet PRIZ spatial light modulator is included. In image pattern recognition, a unified formulation of four different and new types of synthetic discriminant functions is advanced. These include synthetic discriminant functions for intra and inter-class pattern recognition and multi-class pattern recognition. In the area of image pattern recognition, we also advance new statistical synthetic discriminant function filter concepts and a new principal component synthetic discriminant function. These analyses utilize new performance measures and new image models. Conventional holographic pattern recognition research conducted under AFOSR support is also reviewed. Our new AFOSR optical signal processing research concerns optical matrix-vector processors. Initial research in this area includes fabrication of a fiber-optic microprocessor-based iterative optical processor and its use in adaptive phased array radar processing and for the calculation of eigenvalues and eigenvectors of a matrix.

  8. Individual recognition between mother and infant bats (Myotis)

    NASA Technical Reports Server (NTRS)

    Turner, D.; Shaughnessy, A.; Gould, E.

    1972-01-01

    The recognition process and the basis for that recognition, in brown bats, between mother and infant are analyzed. Two parameters, ultrasonic communication and olfactory stimuli, are investigated. The test animals were not allowed any visual contact. It was concluded that individual recognition between mother and infant occurred. However, it could not be determined if the recognition was based on ultrasonic signals or olfactory stimuli.

  9. 29 CFR 29.13 - Recognition of State Apprenticeship Agencies.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 29 Labor 1 2012-07-01 2012-07-01 false Recognition of State Apprenticeship Agencies. 29.13 Section 29.13 Labor Office of the Secretary of Labor LABOR STANDARDS FOR THE REGISTRATION OF APPRENTICESHIP PROGRAMS § 29.13 Recognition of State Apprenticeship Agencies. (a) Recognition. The Department may exercise its authority to grant recognition to...

  10. Recognition Failure and the Composite Memory Trace in CHARM.

    ERIC Educational Resources Information Center

    Metcalfe, Janet

    1991-01-01

    The relationship between recognition and recall, especially the orderly recognition-failure function relating recognition and the recognizability of recallable words, was investigated using a composite holographic associative recall-recognition memory model (CHARM) in 10 series of computer simulations. Support for the model is demonstrated. (SLD)

  11. K(+)-recognition capsules with squirting release mechanisms.

    PubMed

    Liu, Zhuang; Liu, Li; Ju, Xiao-Jie; Xie, Rui; Zhang, Bao; Chu, Liang-Yin

    2011-12-01

    K(+)-recognition capsules are developed to translate K(+)-recognition into a squirting release function. Upon recognition of K(+), the capsules shrink rapidly and squirt out encapsulated oil cores due to the cooperative interaction of host-guest complexation and phase transition in capsule membranes. The capsules provide a promising model for K(+)-recognition smart functional systems. PMID:22001936

  12. Stereochemical Recognition of Helicenes on Metal Surfaces.

    PubMed

    Ernst, Karl-Heinz

    2016-06-21

    The chiral recognition among biomolecules is fundamentally important for many processes of life, including the stereochemistry of evolution. Of special interest is chiral recognition during crystallization of racemates, when either homochiral recognition leads to a conglomerate of homochiral crystals or heterochiral recognition dominates resulting in a racemic compound. The complex nature of molecular recognition at the level of nucleation and crystal growth renders it difficult to understand and calls for manageable model systems. Notably, the approach of studying aggregation of molecules at surfaces under well-defined conditions includes the benefit of the availability of a multitude of highly sensitive investigation methods, of which scanning tunneling microscopy (STM) with its submolecular resolution is tremendously valuable. Heterogeneous nucleation at surfaces is strongly favored over homogeneous nucleation in solution; hence, surfaces are significantly involved in stereochemical recognition during crystallization. Helicenes are a fascinating class of chiral compounds with outstanding optical activity. These π-conjugated, ortho-fused, aromatic hydrocarbons are promising candidates for organic electronic devices such as sensors, circular dichroic photonics, liquid crystal displays or spin filters. But in particular the defined footprint of their terminal benzo rings on a surface makes them interesting for studying stereochemical recognition with different single crystalline surfaces and the impact this has, in turn, on intermolecular recognition. In this Account, we describe the self-assembly of helicenes on metal surfaces with the focus on stereochemical recognition in two-dimensional structures. Using the isomeric all-carbon helicenes, heptahelicene and dibenzohelicene as examples, different aggregation phenomena on different surfaces of single crystalline copper, silver, and gold are investigated. By means of STM different modes of transmission of

  13. Improving protein fold recognition by random forest

    PubMed Central

    2014-01-01

    Background Recognizing the correct structural fold among known template protein structures for a target protein (i.e. fold recognition) is essential for template-based protein structure modeling. Since the fold recognition problem can be defined as a binary classification problem of predicting whether or not the unknown fold of a target protein is similar to an already known template protein structure in a library, machine learning methods have been effectively applied to tackle this problem. In our work, we developed RF-Fold that uses random forest - one of the most powerful and scalable machine learning classification methods - to recognize protein folds. Results RF-Fold consists of hundreds of decision trees that can be trained efficiently on very large datasets to make accurate predictions on a highly imbalanced dataset. We evaluated RF-Fold on the standard Lindahl's benchmark dataset comprised of 976 × 975 target-template protein pairs through cross-validation. Compared with 17 different fold recognition methods, the performance of RF-Fold is generally comparable to the best performance in fold recognition of different difficulty ranging from the easiest family level, the medium-hard superfamily level, and to the hardest fold level. Based on the top-one template protein ranked by RF-Fold, the correct recognition rate is 84.5%, 63.4%, and 40.8% at family, superfamily, and fold levels, respectively. Based on the top-five template protein folds ranked by RF-Fold, the correct recognition rate increases to 91.5%, 79.3% and 58.3% at family, superfamily, and fold levels. Conclusions The good performance achieved by the RF-Fold demonstrates the random forest's effectiveness for protein fold recognition. PMID:25350499

  14. Impaired picture recognition in transient epileptic amnesia.

    PubMed

    Dewar, Michaela; Hoefeijzers, Serge; Zeman, Adam; Butler, Christopher; Della Sala, Sergio

    2015-01-01

    Transient epileptic amnesia (TEA) is an epileptic syndrome characterized by recurrent, brief episodes of amnesia. Transient epileptic amnesia is often associated with the rapid decline in recall of new information over hours to days (accelerated long-term forgetting - 'ALF'). It remains unknown how recognition memory is affected in TEA over time. Here, we report a systematic study of picture recognition in patients with TEA over the course of one week. Sixteen patients with TEA and 16 matched controls were presented with 300 photos of everyday life scenes. Yes/no picture recognition was tested 5min, 2.5h, 7.5h, 24h, and 1week after picture presentation using a subset of target pictures as well as similar and different foils. Picture recognition was impaired in the patient group at all test times, including the 5-minute test, but it declined normally over the course of 1week. This impairment was associated predominantly with an increased false alarm rate, especially for similar foils. High performance on a control test indicates that this impairment was not associated with perceptual or discrimination deficits. Our findings suggest that, at least in some TEA patients with ALF in verbal recall, picture recognition does not decline more rapidly than in controls over 1week. However, our findings of an early picture recognition deficit suggest that new visual memories are impoverished after minutes in TEA. This could be the result of deficient encoding or impaired early consolidation. The early picture recognition deficit observed could reflect either the early stages of the process that leads to ALF or a separable deficit of anterograde memory in TEA. Lastly, our study suggests that at least some patients with TEA are prone to falsely recognizing new everyday visual information that they have not in fact seen previously. This deficit, alongside their ALF in free recall, likely affects everyday memory performance. PMID:25506793

  15. Semantic pyramids for gender and action recognition.

    PubMed

    Khan, Fahad Shahbaz; van de Weijer, Joost; Anwer, Rao Muhammad; Felsberg, Michael; Gatta, Carlo

    2014-08-01

    Person description is a challenging problem in computer vision. We investigated two major aspects of person description: 1) gender and 2) action recognition in still images. Most state-of-the-art approaches for gender and action recognition rely on the description of a single body part, such as face or full-body. However, relying on a single body part is suboptimal due to significant variations in scale, viewpoint, and pose in real-world images. This paper proposes a semantic pyramid approach for pose normalization. Our approach is fully automatic and based on combining information from full-body, upper-body, and face regions for gender and action recognition in still images. The proposed approach does not require any annotations for upper-body and face of a person. Instead, we rely on pretrained state-of-the-art upper-body and face detectors to automatically extract semantic information of a person. Given multiple bounding boxes from each body part detector, we then propose a simple method to select the best candidate bounding box, which is used for feature extraction. Finally, the extracted features from the full-body, upper-body, and face regions are combined into a single representation for classification. To validate the proposed approach for gender recognition, experiments are performed on three large data sets namely: 1) human attribute; 2) head-shoulder; and 3) proxemics. For action recognition, we perform experiments on four data sets most used for benchmarking action recognition in still images: 1) Sports; 2) Willow; 3) PASCAL VOC 2010; and 4) Stanford-40. Our experiments clearly demonstrate that the proposed approach, despite its simplicity, outperforms state-of-the-art methods for gender and action recognition. PMID:24956369

  16. Contextual Modulation of Biases in Face Recognition

    PubMed Central

    Felisberti, Fatima Maria; Pavey, Louisa

    2010-01-01

    Background The ability to recognize the faces of potential cooperators and cheaters is fundamental to social exchanges, given that cooperation for mutual benefit is expected. Studies addressing biases in face recognition have so far proved inconclusive, with reports of biases towards faces of cheaters, biases towards faces of cooperators, or no biases at all. This study attempts to uncover possible causes underlying such discrepancies. Methodology and Findings Four experiments were designed to investigate biases in face recognition during social exchanges when behavioral descriptors (prosocial, antisocial or neutral) embedded in different scenarios were tagged to faces during memorization. Face recognition, measured as accuracy and response latency, was tested with modified yes-no, forced-choice and recall tasks (N = 174). An enhanced recognition of faces tagged with prosocial descriptors was observed when the encoding scenario involved financial transactions and the rules of the social contract were not explicit (experiments 1 and 2). Such bias was eliminated or attenuated by making participants explicitly aware of “cooperative”, “cheating” and “neutral/indifferent” behaviors via a pre-test questionnaire and then adding such tags to behavioral descriptors (experiment 3). Further, in a social judgment scenario with descriptors of salient moral behaviors, recognition of antisocial and prosocial faces was similar, but significantly better than neutral faces (experiment 4). Conclusion The results highlight the relevance of descriptors and scenarios of social exchange in face recognition, when the frequency of prosocial and antisocial individuals in a group is similar. Recognition biases towards prosocial faces emerged when descriptors did not state the rules of a social contract or the moral status of a behavior, and they point to the existence of broad and flexible cognitive abilities finely tuned to minor changes in social context. PMID:20886086

  17. RIG-I in RNA virus recognition.

    PubMed

    Kell, Alison M; Gale, Michael

    2015-05-01

    Antiviral immunity is initiated upon host recognition of viral products via non-self molecular patterns known as pathogen-associated molecular patterns (PAMPs). Such recognition initiates signaling cascades that induce intracellular innate immune defenses and an inflammatory response that facilitates development of the acquired immune response. The retinoic acid-inducible gene I (RIG-I) and the RIG-I-like receptor (RLR) protein family are key cytoplasmic pathogen recognition receptors that are implicated in the recognition of viruses across genera and virus families, including functioning as major sensors of RNA viruses, and promoting recognition of some DNA viruses. RIG-I, the charter member of the RLR family, is activated upon binding to PAMP RNA. Activated RIG-I signals by interacting with the adapter protein MAVS leading to a signaling cascade that activates the transcription factors IRF3 and NF-κB. These actions induce the expression of antiviral gene products and the production of type I and III interferons that lead to an antiviral state in the infected cell and surrounding tissue. RIG-I signaling is essential for the control of infection by many RNA viruses. Recently, RIG-I crosstalk with other pathogen recognition receptors and components of the inflammasome has been described. In this review, we discuss the current knowledge regarding the role of RIG-I in recognition of a variety of virus families and its role in programming the adaptive immune response through cross-talk with parallel arms of the innate immune system, including how RIG-I can be leveraged for antiviral therapy. PMID:25749629

  18. RIG-I in RNA virus recognition

    PubMed Central

    Kell, Alison M.; Gale, Michael

    2015-01-01

    Antiviral immunity is initiated upon host recognition of viral products via non-self molecular patterns known as pathogen-associated molecular patterns (PAMPs). Such recognition initiates signaling cascades that induce intracellular innate immune defenses and an inflammatory response that facilitates development of the acquired immune response. The retinoic acid-inducible gene I (RIG-I) and the RIG-I-like receptor (RLR) protein family are key cytoplasmic pathogen recognition receptors that are implicated in the recognition of viruses across genera and virus families, including functioning as major sensors of RNA viruses, and promoting recognition of some DNA viruses. RIG-I, the charter member of the RLR family, is activated upon binding to PAMP RNA. Activated RIG-I signals by interacting with the adapter protein MAVS leading to a signaling cascade that activates the transcription factors IRF3 and NF-κB. These actions induce the expression of antiviral gene products and the production of type I and III interferons that lead to an antiviral state in the infected cell and surrounding tissue. RIG-I signaling is essential for the control of infection by many RNA viruses. Recently, RIG-I crosstalk with other pathogen recognition receptors and components of the inflammasome has been described. In this review, we discuss the current knowledge regarding the role of RIG-I in recognition of a variety of virus families and its role in programming the adaptive immune response through cross-talk with parallel arms of the innate immune system, including how RIG-I can be leveraged for antiviral therapy. PMID:25749629

  19. What Types of Visual Recognition Tasks Are Mediated by the Neural Subsystem that Subserves Face Recognition?

    ERIC Educational Resources Information Center

    Brooks, Brian E.; Cooper, Eric E.

    2006-01-01

    Three divided visual field experiments tested current hypotheses about the types of visual shape representation tasks that recruit the cognitive and neural mechanisms underlying face recognition. Experiment 1 found a right hemisphere advantage for subordinate but not basic-level face recognition. Experiment 2 found a right hemisphere advantage for…

  20. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2010 CFR

    2010-01-01

    ... 10 Energy 3 2010-01-01 2010-01-01 false Procedures for recognition and withdrawal of recognition of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT...

  1. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2011 CFR

    2011-01-01

    ... 10 Energy 3 2011-01-01 2011-01-01 false Procedures for recognition and withdrawal of recognition of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT...

  2. 10 CFR 431.21 - Procedures for recognition and withdrawal of recognition of accreditation bodies and...

    Code of Federal Regulations, 2014 CFR

    2014-01-01

    ... 10 Energy 3 2014-01-01 2014-01-01 false Procedures for recognition and withdrawal of recognition of accreditation bodies and certification programs. 431.21 Section 431.21 Energy DEPARTMENT OF ENERGY ENERGY CONSERVATION ENERGY EFFICIENCY PROGRAM FOR CERTAIN COMMERCIAL AND INDUSTRIAL EQUIPMENT Electric Motors Test Procedures, Materials...

  3. A motivational determinant of facial emotion recognition: regulatory focus affects recognition of emotions in faces.

    PubMed

    Sassenrath, Claudia; Sassenberg, Kai; Ray, Devin G; Scheiter, Katharina; Jarodzka, Halszka

    2014-01-01

    Two studies examined an unexplored motivational determinant of facial emotion recognition: observer regulatory focus. It was predicted that a promotion focus would enhance facial emotion recognition relative to a prevention focus because the attentional strategies associated with promotion focus enhance performance on well-learned or innate tasks - such as facial emotion recognition. In Study 1, a promotion or a prevention focus was experimentally induced and better facial emotion recognition was observed in a promotion focus compared to a prevention focus. In Study 2, individual differences in chronic regulatory focus were assessed and attention allocation was measured using eye tracking during the facial emotion recognition task. Results indicated that the positive relation between a promotion focus and facial emotion recognition is mediated by shorter fixation duration on the face which reflects a pattern of attention allocation matched to the eager strategy in a promotion focus (i.e., striving to make hits). A prevention focus did not have an impact neither on perceptual processing nor on facial emotion recognition. Taken together, these findings demonstrate important mechanisms and consequences of observer motivational orientation for facial emotion recognition. PMID:25380247

  4. Pupil dilation during recognition memory: Isolating unexpected recognition from judgment uncertainty.

    PubMed

    Mill, Ravi D; O'Connor, Akira R; Dobbins, Ian G

    2016-09-01

    Optimally discriminating familiar from novel stimuli demands a decision-making process informed by prior expectations. Here we demonstrate that pupillary dilation (PD) responses during recognition memory decisions are modulated by expectations, and more specifically, that pupil dilation increases for unexpected compared to expected recognition. Furthermore, multi-level modeling demonstrated that the time course of the dilation during each individual trial contains separable early and late dilation components, with the early amplitude capturing unexpected recognition, and the later trailing slope reflecting general judgment uncertainty or effort. This is the first demonstration that the early dilation response during recognition is dependent upon observer expectations and that separate recognition expectation and judgment uncertainty components are present in the dilation time course of every trial. The findings provide novel insights into adaptive memory-linked orienting mechanisms as well as the general cognitive underpinnings of the pupillary index of autonomic nervous system activity. PMID:27253862

  5. Practical vision based degraded text recognition system

    NASA Astrophysics Data System (ADS)

    Mohammad, Khader; Agaian, Sos; Saleh, Hani

    2011-02-01

    Rapid growth and progress in the medical, industrial, security and technology fields means more and more consideration for the use of camera based optical character recognition (OCR) Applying OCR to scanned documents is quite mature, and there are many commercial and research products available on this topic. These products achieve acceptable recognition accuracy and reasonable processing times especially with trained software, and constrained text characteristics. Even though the application space for OCR is huge, it is quite challenging to design a single system that is capable of performing automatic OCR for text embedded in an image irrespective of the application. Challenges for OCR systems include; images are taken under natural real world conditions, Surface curvature, text orientation, font, size, lighting conditions, and noise. These and many other conditions make it extremely difficult to achieve reasonable character recognition. Performance for conventional OCR systems drops dramatically as the degradation level of the text image quality increases. In this paper, a new recognition method is proposed to recognize solid or dotted line degraded characters. The degraded text string is localized and segmented using a new algorithm. The new method was implemented and tested using a development framework system that is capable of performing OCR on camera captured images. The framework allows parameter tuning of the image-processing algorithm based on a training set of camera-captured text images. Novel methods were used for enhancement, text localization and the segmentation algorithm which enables building a custom system that is capable of performing automatic OCR which can be used for different applications. The developed framework system includes: new image enhancement, filtering, and segmentation techniques which enabled higher recognition accuracies, faster processing time, and lower energy consumption, compared with the best state of the art published

  6. Active place recognition using image signatures

    NASA Astrophysics Data System (ADS)

    Engelson, Sean P.

    1992-11-01

    For reliable navigation, a mobile robot needs to be able to recognize where it is in the world. We previously described an efficient and effective image-based representation of perceptual information for place recognition. Each place is associated with a set of stored image signatures, each a matrix of numbers derived by evaluating some measurement functions over large blocks of pixels. One difficulty, though, is the large number of inherently ambiguous signatures which bloats the database and makes recognition more difficult. Furthermore, since small differences in orientation can produce very different images, reliable recognition requires many images. These problems can be ameliorated by using active methods to select the best signatures to use for the recognition. Two criteria for good images are distinctiveness (is the scene distinguishable from others?) and stability (how much do small viewpoint motions change image recognizability?). We formulate several heuristic distinctiveness metrics which are good predictors of real image distinctiveness. These functions are then used to direct the motion of the camera to find locally distinctive views for use in recognition. This method also produces some modicum of stability, since it uses a form of local optimization. We present the results of applying this method with a camera mounted on a pan-tilt platform.

  7. Speech recognition system for an automotive vehicle

    SciTech Connect

    Noso, K.; Futami, T.

    1987-01-13

    A speech recognition system is described for an automotive vehicle for activating vehicle actuators in response to predetermined spoken instructions supplied to the system via a microphone, which comprises: (a) a manually controlled record switch for deriving a record signal when activated; (b) a manually controlled recognition switch for deriving a recognition signal when activated; (c) a speech recognizer for sequentially recording reference spoken instructions whenever one reference spoken instruction is supplied to the system through the microphone while the record switch is activated, a memory having a storage area for each spoken instruction, and means for shifting access to each storage area for each spoken instruction has been recorded in the storage area provided therefore. A means is included for activating vehicle actuators sequentially whenever one recognition spoken instruction is supplied to the system via the microphone while the recognition switch is activated and when the spoken instruction to be recognized is similar to the reference spoken instruction; and (d) means for deriving skip instruction signal and for coupling the skip instruction signal to the speech recognizer to shift access from a currently accessed storage area for recording a current reference spoken instruction to a succeeding storage area for recording a succeeding reference spoken instruction even when the current reference spoken instruction is not supplied to the system through the microphone.

  8. Timecourse of neural signatures of object recognition.

    PubMed

    Johnson, Jeffrey S; Olshausen, Bruno A

    2003-01-01

    How long does it take for the human visual system to recognize objects? This issue is important for understanding visual cortical function as it places constraints on models of the information processing underlying recognition. We designed a series of event-related potential (ERP) experiments to measure the timecourse of electrophysiological correlates of object recognition. We find two distinct types of components in the ERP recorded during categorization of natural images. One is an early presentation-locked signal arising around 135 ms that is present when there are low-level feature differences between images. The other is a later, recognition-related component arising between 150-300 ms. Unlike the early component, the latency of the later component covaries with the subsequent reaction time. In contrast to previous studies suggesting that the early, presentation-locked component of neural activity is correlated to recognition, these results imply that the neural signatures of recognition have a substantially later and variable time of onset. PMID:14507255

  9. Development of individually distinct recognition cues.

    PubMed

    Mateo, Jill M

    2006-11-01

    Despite extensive research on the functions of kin recognition, little is known about ontogenetic changes in the cues mediating such recognition. In Belding's ground squirrels, Spermophilus beldingi, secretions from oral glands are both individually distinct and kin distinct, and function in social recognition across many contexts. Behavioral studies of recognition and kin preferences suggest that these cues may change across development, particularly around the time of weaning and emergence from natal burrows (around 25 days of age). I used an habituation-discrimination task with captive S. beldingi, presenting subjects with odors collected from a pair of pups at several ages across early development. I found that at 21 days of age, but not at 7 or 14, young produce detectable odors. Odors are not individually distinct, however, until 28 days of age, after young have emerged from their burrows and begun foraging. In addition, an individual's odor continues to develop after emergence: odors produced by an individual at 20 and 40 days of age are perceived as dissimilar, yet odors produced at 28 and 40 days are treated as similar. Developmental changes in odors provide a proximate explanation for why S. beldingi littermate preferences are not consolidated until after natal emergence, and demonstrate that conspecifics must update their recognition templates as young develop. PMID:17016836

  10. Pseudo-Gabor wavelet for face recognition

    NASA Astrophysics Data System (ADS)

    Xie, Xudong; Liu, Wentao; Lam, Kin-Man

    2013-04-01

    An efficient face-recognition algorithm is proposed, which not only possesses the advantages of linear subspace analysis approaches-such as low computational complexity-but also has the advantage of a high recognition performance with the wavelet-based algorithms. Based on the linearity of Gabor-wavelet transformation and some basic assumptions on face images, we can extract pseudo-Gabor features from the face images without performing any complex Gabor-wavelet transformations. The computational complexity can therefore be reduced while a high recognition performance is still maintained by using the principal component analysis (PCA) method. The proposed algorithm is evaluated based on the Yale database, the Caltech database, the ORL database, the AR database, and the Facial Recognition Technology database, and is compared with several different face recognition methods such as PCA, Gabor wavelets plus PCA, kernel PCA, locality preserving projection, and dual-tree complex wavelet transformation plus PCA. Experiments show that consistent and promising results are obtained.

  11. Automatic TLI recognition system, general description

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report is a general description of an automatic target recognition system developed at the Idaho National Engineering Laboratory for the Department of Energy. A user`s manual is a separate volume, Automatic TLI Recognition System, User`s Guide, and a programmer`s manual is Automatic TLI Recognition System, Programmer`s Guide. This system was designed as an automatic target recognition system for fast screening of large amounts of multi-sensor image data, based on low-cost parallel processors. This system naturally incorporates image data fusion, and it gives uncertainty estimates. It is relatively low cost, compact, and transportable. The software is easily enhanced to expand the system`s capabilities, and the hardware is easily expandable to increase the system`s speed. In addition to its primary function as a trainable target recognition system, this is also a versatile, general-purpose tool for image manipulation and analysis, which can be either keyboard-driven or script-driven. This report includes descriptions of three variants of the computer hardware, a description of the mathematical basis if the training process, and a description with examples of the system capabilities.

  12. Recall and recognition hypermnesia for Socratic stimuli.

    PubMed

    Kazén, Miguel; Solís-Macías, Víctor M

    2016-01-01

    In two experiments, we investigate hypermnesia, net memory improvements with repeated testing of the same material after a single study trial. In the first experiment, we found hypermnesia across three trials for the recall of word solutions to Socratic stimuli (dictionary-like definitions of concepts) replicating Erdelyi, Buschke, and Finkelstein and, for the first time using these materials, for their recognition. In the second experiment, we had two "yes/no" recognition groups, a Socratic stimuli group presented with concrete and abstract verbal materials and a word-only control group. Using signal detection measures, we found hypermnesia for concrete Socratic stimuli-and stable performance for abstract stimuli across three recognition tests. The control group showed memory decrements across tests. We interpret these findings with the alternative retrieval pathways (ARP) hypothesis, contrasting it with alternative theories of hypermnesia, such as depth of processing, generation and retrieve-recognise. We conclude that recognition hypermnesia for concrete Socratic stimuli is a reliable phenomenon, which we found in two experiments involving both forced-choice and yes/no recognition procedures. PMID:25523628

  13. Action recognition in the visual periphery.

    PubMed

    Fademrecht, Laura; Bülthoff, Isabelle; de la Rosa, Stephan

    2016-01-01

    Recognizing whether the gestures of somebody mean a greeting or a threat is crucial for social interactions. In real life, action recognition occurs over the entire visual field. In contrast, much of the previous research on action recognition has primarily focused on central vision. Here our goal is to examine what can be perceived about an action outside of foveal vision. Specifically, we probed the valence as well as first level and second level recognition of social actions (handshake, hugging, waving, punching, slapping, and kicking) at 0° (fovea/fixation), 15°, 30°, 45°, and 60° of eccentricity with dynamic (Experiment 1) and dynamic and static (Experiment 2) actions. To assess peripheral vision under conditions of good ecological validity, these actions were carried out by a life-size human stick figure on a large screen. In both experiments, recognition performance was surprisingly high (more than 66% correct) up to 30° of eccentricity for all recognition tasks and followed a nonlinear decline with increasing eccentricities. PMID:26913625

  14. Discrimination within Recognition Memory in Schizophrenia

    PubMed Central

    McGuire, Kathryn A.; Blahnik, Melanie M.; Sponheim, Scott R.

    2013-01-01

    Episodic memory is one of the most affected cognitive domains in schizophrenia. First-degree biological relatives of individuals with schizophrenia also have been found to exhibit a similar, but milder, episodic memory deficit. Unlike most studies that focus on the percent of previously presented items recognized, the current investigation sought to further elucidate the nature of memory dysfunction associated with schizophrenia by examining the discrimination of old and new material during recognition (measured by d') to consider false recognition of new items. Using the Recurring Figures Test and the California Verbal Learning Test (CVLT), we studied a sample of schizophrenia probands and the first-degree biological relatives of patients with schizophrenia, as well as probands with bipolar disorder and first-degree biological relatives to assess the specificity of recognition memory dysfunction to schizophrenia. The schizophrenia sample had poorer recognition discrimination in both nonverbal and verbal modalities; no such deficits were identified in first-degree biological relatives or bipolar disorder probands. Discrimination in schizophrenia and bipolar probands failed to benefit from the geometric structure in the designs in the manner that controls did on the nonverbal test. Females performed better than males in recognition of geometric designs. Episodic memory dysfunction in schizophrenia is present for a variety of stimulus domains and reflects poor use of item content to increase discrimination of old and new items. PMID:25379239

  15. The perirhinal cortex and recognition memory interference

    PubMed Central

    Watson, H.C.; Lee, A. C. H.

    2013-01-01

    There has recently been an increase in interest in the effects of visual interference on memory processing, with the aim of eluciating the role of the perirhinal cortex (PRC) in recognition memory. One view argues that the PRC processes highly complex conjunctions of object features, and recent evidence from rodents suggests that these representations may be vital for buffering against the effects of pre-retrieval interference on object recognition memory. To investigate whether PRC-dependent object representations play a similar role in humans, we used functional magnetic resonance imaging to scan neurologically healthy participants while they carried out a novel interference-match-to-sample task. This paradigm was specifically designed to concurrently assess the impact of object vs. spatial interference, on recognition memory for objects or scenes, while keeping constant the amount of object and scene information presented across all trials. Activity at retrieval was examined, within an anatomically defined PRC region of interest, according to the demand for object or scene memory, following a period of object compared to spatial interference. Critically, we found greater PRC activity for object memory following object interference, compared to object memory following scene interference, and no difference between object and scene interference for scene recognition. These data demonstrate a role for the human PRC following a period of object, but not scene, interference, during object recognition memory, and emphasize the importance of representational content to mnemonic processing. PMID:23447626

  16. Social appraisal influences recognition of emotions.

    PubMed

    Mumenthaler, Christian; Sander, David

    2012-06-01

    The notion of social appraisal emphasizes the importance of a social dimension in appraisal theories of emotion by proposing that the way an individual appraises an event is influenced by the way other individuals appraise and feel about the same event. This study directly tested this proposal by asking participants to recognize dynamic facial expressions of emotion (fear, happiness, or anger in Experiment 1; fear, happiness, anger, or neutral in Experiment 2) in a target face presented at the center of a screen while a contextual face, which appeared simultaneously in the periphery of the screen, expressed an emotion (fear, happiness, anger) or not (neutral) and either looked at the target face or not. We manipulated gaze direction to be able to distinguish between a mere contextual effect (gaze away from both the target face and the participant) and a specific social appraisal effect (gaze toward the target face). Results of both experiments provided evidence for a social appraisal effect in emotion recognition, which differed from the mere effect of contextual information: Whereas facial expressions were identical in both conditions, the direction of the gaze of the contextual face influenced emotion recognition. Social appraisal facilitated the recognition of anger, happiness, and fear when the contextual face expressed the same emotion. This facilitation was stronger than the mere contextual effect. Social appraisal also allowed better recognition of fear when the contextual face expressed anger and better recognition of anger when the contextual face expressed fear. PMID:22288528

  17. Recognition without awareness: Encoding and retrieval factors.

    PubMed

    Craik, Fergus I M; Rose, Nathan S; Gopie, Nigel

    2015-09-01

    The article reports 4 experiments that explore the notion of recognition without awareness using words as the material. Previous work by Voss and associates has shown that complex visual patterns were correctly selected as targets in a 2-alternative forced-choice (2-AFC) recognition test although participants reported that they were guessing. The present experiments sought to extend this earlier work by having participants study words in different ways and then attempt to recognize the words later in a series of 4-alternative forced-choice (4-AFC) tests, some of which contained no target word. The data of interest are cases in which a target was present and participants stated that they were guessing, yet chose the correct item. This value was greater than p = .25 in all conditions of the 4 experiments, demonstrating the phenomenon of recognition without awareness. Whereas Voss and colleagues attributed their findings with kaleidoscope patterns to enhanced processing fluency of perceptual attributes, the main factor associated with different levels of recognition without awareness in the present studies was a variable criterion for the subjective state accompanying selection of the "guess" option, depending on the overall difficulty of the recognition test. We conclude by discussing some implications of the results for the distinction between implicit and explicit memory. PMID:26010824

  18. Pattern activation/recognition theory of mind

    PubMed Central

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a “Pattern Recognition Theory of Mind” that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call “Pattern Activation/Recognition Theory of Mind.” While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

  19. Pattern activation/recognition theory of mind.

    PubMed

    du Castel, Bertrand

    2015-01-01

    In his 2012 book How to Create a Mind, Ray Kurzweil defines a "Pattern Recognition Theory of Mind" that states that the brain uses millions of pattern recognizers, plus modules to check, organize, and augment them. In this article, I further the theory to go beyond pattern recognition and include also pattern activation, thus encompassing both sensory and motor functions. In addition, I treat checking, organizing, and augmentation as patterns of patterns instead of separate modules, therefore handling them the same as patterns in general. Henceforth I put forward a unified theory I call "Pattern Activation/Recognition Theory of Mind." While the original theory was based on hierarchical hidden Markov models, this evolution is based on their precursor: stochastic grammars. I demonstrate that a class of self-describing stochastic grammars allows for unifying pattern activation, recognition, organization, consistency checking, metaphor, and learning, into a single theory that expresses patterns throughout. I have implemented the model as a probabilistic programming language specialized in activation/recognition grammatical and neural operations. I use this prototype to compute and present diagrams for each stochastic grammar and corresponding neural circuit. I then discuss the theory as it relates to artificial network developments, common coding, neural reuse, and unity of mind, concluding by proposing potential paths to validation. PMID:26236228

  20. Visual word recognition across the adult lifespan.

    PubMed

    Cohen-Shikora, Emily R; Balota, David A

    2016-08-01

    The current study examines visual word recognition in a large sample (N = 148) across the adult life span and across a large set of stimuli (N = 1,187) in three different lexical processing tasks (pronunciation, lexical decision, and animacy judgment). Although the focus of the present study is on the influence of word frequency, a diverse set of other variables are examined as the word recognition system ages and acquires more experience with language. Computational models and conceptual theories of visual word recognition and aging make differing predictions for age-related changes in the system. However, these have been difficult to assess because prior studies have produced inconsistent results, possibly because of sample differences, analytic procedures, and/or task-specific processes. The current study confronts these potential differences by using 3 different tasks, treating age and word variables as continuous, and exploring the influence of individual differences such as vocabulary, vision, and working memory. The primary finding is remarkable stability in the influence of a diverse set of variables on visual word recognition across the adult age spectrum. This pattern is discussed in reference to previous inconsistent findings in the literature and implications for current models of visual word recognition. (PsycINFO Database Record PMID:27336629

  1. Speech recognition: Acoustic, phonetic and lexical

    NASA Astrophysics Data System (ADS)

    Zue, V. W.

    1985-10-01

    Our long-term research goal is the development and implementation of speaker-independent continuous speech recognition systems. It is our conviction that proper utilization of speech-specific knowledge is essential for advanced speech recognition systems. With this in mind, we have continued to make progress on the acquisition of acoustic-phonetic and lexical knowledge. We have completed the development of a continuous digit recognition system. The system was constructed to investigate the utilization of acoustic phonetic knowledge in a speech recognition system. Some of the significant development of this study includes a soft-failure procedure for lexical access, and the discovery of a set of acoustic-phonetic features for verification. We have completed a study of the constraints provided by lexical stress on word recognition. We found that lexical stress information alone can, on the average, reduce the number of word candidates from a large dictionary by more than 80%. In conjunction with this study, we successfully developed a system that automatically determines the stress pattern of a word from the acoustic signal.

  2. Acoustic-phonetic representations in word recognition*

    PubMed Central

    PISONI, DAVID B.; LUCE, PAUL A.

    2012-01-01

    This paper reviews what is currently known about the sensory and perceptual input that is made available to the word recognition system by processes typically assumed to be related to speech sound perception. In the first section, we discuss several of the major problems that speech researchers have tried to deal with over the last thirty years. In the second section, we consider one attempt to conceptualize the speech perception process within a theoretical framework that equates processing stages with levels of linguistic analysis. This framework assumes that speech is processed through a series of analytic stages ranging from peripheral auditory processing, acoustic-phonetic and phonological analysis, to word recognition and lexical access. Finally, in the last section, we consider several recent approaches to spoken word recognition and lexical access. We examine a number of claims surrounding the nature of the bottom-up input assumed by these models, postulated perceptual units, and the interaction of different knowledge sources in auditory word recognition. An additional goal of this paper was to establish the need to employ segmental representations in spoken word recognition. PMID:3581727

  3. Exposure effects on music preference and recognition.

    PubMed

    Peretz, I; Gaudreau, D; Bonnel, A M

    1998-09-01

    In three experiments, the effects of exposure to melodies on their subsequent liking and recognition were explored. In each experiment, the subjects first listened to a set of familiar and unfamiliar melodies in a study phase. In the subsequent test phase, the melodies were repeated, along with a set of distractors matched in familiarity. Half the subjects were required to rate their liking of each melody, and half had to identify the melodies they had heard earlier in the study phase. Repetition of the studied melodies was found to increase liking of the unfamiliar melodies in the affect task and to be best for detection of familiar melodies in the recognition task (Experiments 1, 2, and 3). These memory effects were found to fade at different time delays between study and test in the affect and recognition tasks, with the latter leading to the most persistent effects (Experiment 2). Both study-to-test changes in melody timbre and manipulation of study tasks had a marked impact on recognition and little influence on liking judgments (Experiment 3). Thus, all manipulated variables were found to dissociate the memory effects in the two tasks. The results are consistent with the view that memory effects in the affect and recognition tasks pertain to the implicit and explicit forms of memory, respectively. Part of the results are, however, at variance with the literature on implicit and explicit memory in the auditory domain. Attribution of these differences to the use of musical material is discussed. PMID:9796224

  4. Brain-wave recognition of sentences

    PubMed Central

    Suppes, Patrick; Han, Bing; Lu, Zhong-Lin

    1998-01-01

    Electrical and magnetic brain waves of two subjects were recorded for the purpose of recognizing which one of 12 sentences or seven words auditorily presented was processed. The analysis consisted of averaging over trials to create prototypes and test samples, to each of which a Fourier transform was applied, followed by filtering and an inverse transformation to the time domain. The filters used were optimal predictive filters, selected for each subject. A still further improvement was obtained by taking differences between recordings of two electrodes to obtain bipolar pairs that then were used for the same analysis. Recognition rates, based on a least-squares criterion, varied, but the best were above 90%. The first words of prototypes of sentences also were cut and pasted to test, at least partially, the invariance of a word’s brain wave in different sentence contexts. The best result was above 80% correct recognition. Test samples made up only of individual trials also were analyzed. The best result was 134 correct of 288 (47%), which is promising, given that the expected recognition number by chance is just 24 (or 8.3%). The work reported in this paper extends our earlier work on brain-wave recognition of words only. The recognition rates reported here further strengthen the case that recordings of electric brain waves of words or sentences, together with extensive mathematical and statistical analysis, can be the basis of new developments in our understanding of brain processing of language. PMID:9861061

  5. Feature quality-based multimodal unconstrained eye recognition

    NASA Astrophysics Data System (ADS)

    Zhou, Zhi; Du, Eliza Y.; Lin, Yong; Thomas, N. Luke; Belcher, Craig; Delp, Edward J.

    2013-05-01

    Iris recognition has been tested to the most accurate biometrics using high resolution near infrared images. However, it does not work well under visible wavelength illumination. Sclera recognition, however, has been shown to achieve reasonable recognition accuracy under visible wavelengths. Combining iris and sclera recognition together can achieve better recognition accuracy. However, image quality can significantly affect the recognition accuracy. Moreover, in unconstrained situations, the acquired eye images may not be frontally facing. In this research, we proposed a feature quality-based multimodal unconstrained eye recognition method that combine the respective strengths of iris recognition and sclera recognition for human identification and can work with frontal and off-angle eye images. The research results show that the proposed method is very promising.

  6. Facial expression recognition based on improved DAGSVM

    NASA Astrophysics Data System (ADS)

    Luo, Yuan; Cui, Ye; Zhang, Yi

    2014-11-01

    For the cumulative error problem because of randomization sequence of traditional DAGSVM(Directed Acyclic Graph Support Vector Machine) classification, this paper presents an improved DAGSVM expression recognition method. The method uses the distance of class and the standard deviation as the measure of the classer, which minimize the error rate of the upper structure of the classification. At the same time, this paper uses the method which combines discrete cosine transform (Discrete Cosine Transform, DCT) with Local Binary Pattern(Local Binary Pattern - LBP) ,to extract expression feature and be the input to improve the DAGSVM classifier for recognition. Experimental results show that compared with other multi-class support vector machine method, improved DAGSVM classifier can achieve higher recognition rate. And when it's used at the platform of the intelligent wheelchair, experiments show that the method has a better robustness.

  7. Biologically inspired emotion recognition from speech

    NASA Astrophysics Data System (ADS)

    Caponetti, Laura; Buscicchio, Cosimo Alessandro; Castellano, Giovanna

    2011-12-01

    Emotion recognition has become a fundamental task in human-computer interaction systems. In this article, we propose an emotion recognition approach based on biologically inspired methods. Specifically, emotion classification is performed using a long short-term memory (LSTM) recurrent neural network which is able to recognize long-range dependencies between successive temporal patterns. We propose to represent data using features derived from two different models: mel-frequency cepstral coefficients (MFCC) and the Lyon cochlear model. In the experimental phase, results obtained from the LSTM network and the two different feature sets are compared, showing that features derived from the Lyon cochlear model give better recognition results in comparison with those obtained with the traditional MFCC representation.

  8. Cognitive and artificial representations in handwriting recognition

    NASA Astrophysics Data System (ADS)

    Lenaghan, Andrew P.; Malyan, Ron

    1996-03-01

    Both cognitive processes and artificial recognition systems may be characterized by the forms of representation they build and manipulate. This paper looks at how handwriting is represented in current recognition systems and the psychological evidence for its representation in the cognitive processes responsible for reading. Empirical psychological work on feature extraction in early visual processing is surveyed to show that a sound psychological basis for feature extraction exists and to describe the features this approach leads to. The first stage of the development of an architecture for a handwriting recognition system which has been strongly influenced by the psychological evidence for the cognitive processes and representations used in early visual processing, is reported. This architecture builds a number of parallel low level feature maps from raw data. These feature maps are thresholded and a region labeling algorithm is used to generate sets of features. Fuzzy logic is used to quantify the uncertainty in the presence of individual features.

  9. Handwriting Moroccan regions recognition using Tifinagh character.

    PubMed

    El Kessab, B; Daoui, C; Bouikhalene, B; Salouan, R

    2015-09-01

    The territorial organization of Morocco during administratives division of 2009 is based on 16 regions. In this work we will create a system of recognition of handwritten words (names of regions) using the Amazigh language is an official language by the Moroccan Royal Institute of Amazigh Culture (IRCAM) (2003a) [1] such as this language is slightly treated by researchers in pattern recognition field that is why we decided to study this language (El Kessab et al., 2013 [3]; El Kessab et al., 2014 [4]) that knowing the state make a decision to computerize the various public sectors by this language. In this context we propose a data set for handwritten Tifinagh regions composed of 1600 image (100 Image for each region). The dataset can be used in one hand to test the efficiency of the Tifinagh region recognition system in extraction of characteristics significatives and the correct identification of each region in classification phase in the other hand. PMID:26966718

  10. Real-time, face recognition technology

    SciTech Connect

    Brady, S.

    1995-11-01

    The Institute for Scientific Computing Research (ISCR) at Lawrence Livermore National Laboratory recently developed the real-time, face recognition technology KEN. KEN uses novel imaging devices such as silicon retinas developed at Caltech or off-the-shelf CCD cameras to acquire images of a face and to compare them to a database of known faces in a robust fashion. The KEN-Online project makes that recognition technology accessible through the World Wide Web (WWW), an internet service that has recently seen explosive growth. A WWW client can submit face images, add them to the database of known faces and submit other pictures that the system tries to recognize. KEN-Online serves to evaluate the recognition technology and grow a large face database. KEN-Online includes the use of public domain tools such as mSQL for its name-database and perl scripts to assist the uploading of images.

  11. Neural circuitry for rat recognition memory

    PubMed Central

    Warburton, E.C.; Brown, M.W.

    2015-01-01

    Information concerning the roles of different brain regions in recognition memory processes is reviewed. The review concentrates on findings from spontaneous recognition memory tasks performed by rats, including memory for single objects, locations, object–location associations and temporal order. Particular emphasis is given to the potential roles of different regions in the circuit of interacting structures involving the perirhinal cortex, hippocampus, medial prefrontal cortex and medial dorsal thalamus in recognition memory for the association of objects and places. It is concluded that while all structures in this circuit play roles critical to such memory, these roles can potentially be differentiated and differences in the underlying synaptic and biochemical processes involved in each region are beginning to be uncovered. PMID:25315129

  12. Investigation of Carbohydrate Recognition via Computer Simulation

    SciTech Connect

    Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; Shen, Tongye

    2015-04-28

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We review the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.

  13. Neural microgenesis of personally familiar face recognition

    PubMed Central

    Ramon, Meike; Vizioli, Luca; Liu-Shuang, Joan; Rossion, Bruno

    2015-01-01

    Despite a wealth of information provided by neuroimaging research, the neural basis of familiar face recognition in humans remains largely unknown. Here, we isolated the discriminative neural responses to unfamiliar and familiar faces by slowly increasing visual information (i.e., high-spatial frequencies) to progressively reveal faces of unfamiliar or personally familiar individuals. Activation in ventral occipitotemporal face-preferential regions increased with visual information, independently of long-term face familiarity. In contrast, medial temporal lobe structures (perirhinal cortex, amygdala, hippocampus) and anterior inferior temporal cortex responded abruptly when sufficient information for familiar face recognition was accumulated. These observations suggest that following detailed analysis of individual faces in core posterior areas of the face-processing network, familiar face recognition emerges categorically in medial temporal and anterior regions of the extended cortical face network. PMID:26283361

  14. Recognition bias and the physical attractiveness stereotype.

    PubMed

    Rohner, Jean-Christophe; Rasmussen, Anders

    2012-06-01

    Previous studies have found a recognition bias for information consistent with the physical attractiveness stereotype (PAS), in which participants believe that they remember that attractive individuals have positive qualities and that unattractive individuals have negative qualities, regardless of what information actually occurred. The purpose of this research was to examine whether recognition bias for PAS congruent information is replicable and invariant across a variety of conditions (i.e. generalizable). The effects of nine different moderator variables were examined in two experiments. With a few exceptions, the effect of PAS congruence on recognition bias was independent of the moderator variables. The results suggest that the tendency to believe that one remembers information consistent with the physical attractiveness stereotype is a robust phenomenon. PMID:22416805

  15. Robust facial expression recognition via compressive sensing.

    PubMed

    Zhang, Shiqing; Zhao, Xiaoming; Lei, Bicheng

    2012-01-01

    Recently, compressive sensing (CS) has attracted increasing attention in the areas of signal processing, computer vision and pattern recognition. In this paper, a new method based on the CS theory is presented for robust facial expression recognition. The CS theory is used to construct a sparse representation classifier (SRC). The effectiveness and robustness of the SRC method is investigated on clean and occluded facial expression images. Three typical facial features, i.e., the raw pixels, Gabor wavelets representation and local binary patterns (LBP), are extracted to evaluate the performance of the SRC method. Compared with the nearest neighbor (NN), linear support vector machines (SVM) and the nearest subspace (NS), experimental results on the popular Cohn-Kanade facial expression database demonstrate that the SRC method obtains better performance and stronger robustness to corruption and occlusion on robust facial expression recognition tasks. PMID:22737035

  16. Investigation of Carbohydrate Recognition via Computer Simulation

    DOE PAGESBeta

    Johnson, Quentin R.; Lindsay, Richard J.; Petridis, Loukas; Shen, Tongye

    2015-04-28

    Carbohydrate recognition by proteins, such as lectins and other (bio)molecules, can be essential for many biological functions. Interest has arisen due to potential protein and drug design and future bioengineering applications. A quantitative measurement of carbohydrate-protein interaction is thus important for the full characterization of sugar recognition. Here, we focus on the aspect of utilizing computer simulations and biophysical models to evaluate the strength and specificity of carbohydrate recognition in this review. With increasing computational resources, better algorithms and refined modeling parameters, using state-of-the-art supercomputers to calculate the strength of the interaction between molecules has become increasingly mainstream. We reviewmore » the current state of this technique and its successful applications for studying protein-sugar interactions in recent years.« less

  17. Human gait recognition based on compactness

    NASA Astrophysics Data System (ADS)

    Chen, Feng; Jiang, Jie; Zhang, Guangjun

    2008-10-01

    Gait recognition is new biological identity technology and widely researched in recent years for its many advantages compared with other biological identity technology. In this paper, we propose a simple but effective feature-compactness for gait recognition. First an improved background subtraction algorithm is used to obtain the silhouettes. Then the compactness is extracted from the images in the gait sequence as the feature vector. In the step of classification, DTW algorithm is adopted to adjust the feature vectors before classifying and two classifiers (NN and ENN) are used as classifiers. Because of the simple features which we choose, it consumes little time for recognition and the results turn out to be encouraging.

  18. Gait Recognition Using Image Self-Similarity

    NASA Astrophysics Data System (ADS)

    BenAbdelkader, Chiraz; Cutler, Ross G.; Davis, Larry S.

    2004-12-01

    Gait is one of the few biometrics that can be measured at a distance, and is hence useful for passive surveillance as well as biometric applications. Gait recognition research is still at its infancy, however, and we have yet to solve the fundamental issue of finding gait features which at once have sufficient discrimination power and can be extracted robustly and accurately from low-resolution video. This paper describes a novel gait recognition technique based on the image self-similarity of a walking person. We contend that the similarity plot encodes a projection of gait dynamics. It is also correspondence-free, robust to segmentation noise, and works well with low-resolution video. The method is tested on multiple data sets of varying sizes and degrees of difficulty. Performance is best for fronto-parallel viewpoints, whereby a recognition rate of 98% is achieved for a data set of 6 people, and 70% for a data set of 54 people.

  19. Extraversion predicts individual differences in face recognition.

    PubMed

    Li, Jingguang; Tian, Moqian; Fang, Huizhen; Xu, Miao; Li, He; Liu, Jia

    2010-07-01

    In daily life, one of the most common social tasks we perform is to recognize faces. However, the relation between face recognition ability and social activities is largely unknown. Here we ask whether individuals with better social skills are also better at recognizing faces. We found that extraverts who have better social skills correctly recognized more faces than introverts. However, this advantage was absent when extraverts were asked to recognize non-social stimuli (e.g., flowers). In particular, the underlying facet that makes extraverts better face recognizers is the gregariousness facet that measures the degree of inter-personal interaction. In addition, the link between extraversion and face recognition ability was independent of general cognitive abilities. These findings provide the first evidence that links face recognition ability to our daily activity in social communication, supporting the hypothesis that extraverts are better at decoding social information than introverts. PMID:20798810

  20. Constructive Autoassociative Neural Network for Facial Recognition

    PubMed Central

    Fernandes, Bruno J. T.; Cavalcanti, George D. C.; Ren, Tsang I.

    2014-01-01

    Autoassociative artificial neural networks have been used in many different computer vision applications. However, it is difficult to define the most suitable neural network architecture because this definition is based on previous knowledge and depends on the problem domain. To address this problem, we propose a constructive autoassociative neural network called CANet (Constructive Autoassociative Neural Network). CANet integrates the concepts of receptive fields and autoassociative memory in a dynamic architecture that changes the configuration of the receptive fields by adding new neurons in the hidden layer, while a pruning algorithm removes neurons from the output layer. Neurons in the CANet output layer present lateral inhibitory connections that improve the recognition rate. Experiments in face recognition and facial expression recognition show that the CANet outperforms other methods presented in the literature. PMID:25542018

  1. Recognition and language in low functioning autism.

    PubMed

    Boucher, Jill; Bigham, Sally; Mayes, Andrew; Muskett, Tom

    2008-08-01

    The hypothesis that a pervasive impairment of declarative memory contributes to language impairment in low functioning autism (LFA) was tested. Participants with LFA, high functioning autism (HFA), intellectual disability (ID) without autism, and typical development (TD) were given two recognition tests and four tests of lexical understanding. It was predicted that recognition would be impaired in the LFA group relative to the HFA and TD groups but not the ID group, and that recognition would correlate with lexical knowledge in the LFA group but none of the other groups. These predictions were supported except that the HFA group performed more similarly to the LFA group than expected, a finding interpreted in terms of selectively impaired episodic memory. PMID:18064549

  2. A Survey on Automatic Speaker Recognition Systems

    NASA Astrophysics Data System (ADS)

    Saquib, Zia; Salam, Nirmala; Nair, Rekha P.; Pandey, Nipun; Joshi, Akanksha

    Human listeners are capable of identifying a speaker, over the telephone or an entryway out of sight, by listening to the voice of the speaker. Achieving this intrinsic human specific capability is a major challenge for Voice Biometrics. Like human listeners, voice biometrics uses the features of a person's voice to ascertain the speaker's identity. The best-known commercialized forms of voice Biometrics is Speaker Recognition System (SRS). Speaker recognition is the computing task of validating a user's claimed identity using characteristics extracted from their voices. This literature survey paper gives brief introduction on SRS, and then discusses general architecture of SRS, biometric standards relevant to voice/speech, typical applications of SRS, and current research in Speaker Recognition Systems. We have also surveyed various approaches for SRS.

  3. Molecular Recognition of Lys and Arg Methylation.

    PubMed

    Beaver, Joshua E; Waters, Marcey L

    2016-03-18

    A network of reader proteins and enzymes precisely controls gene transcription through the dynamic addition, removal, and recognition of post-translational modifications (PTMs) of histone tails. Histone PTMs work in concert with this network to regulate gene transcription through the histone code, and the dysregulation of PTM maintenance is linked to a large number of diseases, including many types of cancer. A wealth of research aims to elucidate the functions of this code, but our understanding of the effects of PTMs, specifically the methylation of lysine (Lys) and arginine (Arg), is lacking. The development of new tools to study PTMs relies on a sophisticated understanding of the mechanisms that drive protein and small molecule recognition in water. In this review, we outline the physical organic concepts that drive the molecular recognition of Lys and Arg methylation by reader proteins and draw comparisons to the binding mechanisms of small molecule receptors for methylated Lys and Arg that have been developed recently. PMID:26759915

  4. The effects of conformity on recognition judgements.

    PubMed

    Reysen, Matthew B

    2005-01-01

    Schneider and Watkins (1996) demonstrated that participants' recognition performance can be affected by responses generated by a confederate. However, it remains uncertain whether the confederate's responses actually change the participants' memories or whether participants simply attempt to conform to the confederate. The present experiments examined this issue by having participants complete a final individual recognition test following a recognition test in which the participants worked with a virtual confederate. The results suggest that responses from virtual confederates affect participants' performance in ways similar to actual confederates and that conforming to a virtual confederate's responses does appear to result in actual deficits in memory. More specifically, it impairs participants' ability to correctly recognise material presented earlier. PMID:15724910

  5. Analysis of Human Electrocardiogram for Biometric Recognition

    NASA Astrophysics Data System (ADS)

    Wang, Yongjin; Agrafioti, Foteini; Hatzinakos, Dimitrios; Plataniotis, Konstantinos N.

    2007-12-01

    Security concerns increase as the technology for falsification advances. There are strong evidences that a difficult to falsify biometric trait, the human heartbeat, can be used for identity recognition. Existing solutions for biometric recognition from electrocardiogram (ECG) signals are based on temporal and amplitude distances between detected fiducial points. Such methods rely heavily on the accuracy of fiducial detection, which is still an open problem due to the difficulty in exact localization of wave boundaries. This paper presents a systematic analysis for human identification from ECG data. A fiducial-detection-based framework that incorporates analytic and appearance attributes is first introduced. The appearance-based approach needs detection of one fiducial point only. Further, to completely relax the detection of fiducial points, a new approach based on autocorrelation (AC) in conjunction with discrete cosine transform (DCT) is proposed. Experimentation demonstrates that the AC/DCT method produces comparable recognition accuracy with the fiducial-detection-based approach.

  6. Experiences in Pattern Recognition for Machine Olfaction

    NASA Astrophysics Data System (ADS)

    Bessant, C.

    2011-09-01

    Pattern recognition is essential for translating complex olfactory sensor responses into simple outputs that are relevant to users. Many approaches to pattern recognition have been applied in this field, including multivariate statistics (e.g. discriminant analysis), artificial neural networks (ANNs) and support vector machines (SVMs). Reviewing our experience of using these techniques with many different sensor systems reveals some useful insights. Most importantly, it is clear beyond any doubt that the quantity and selection of samples used to train and test a pattern recognition system are by far the most important factors in ensuring it performs as accurately and reliably as possible. Here we present evidence for this assertion and make suggestions for best practice based on these findings.

  7. When recognition memory is independent of hippocampal function

    PubMed Central

    Smith, Christine N.; Jeneson, Annette; Frascino, Jennifer C.; Kirwan, C. Brock; Hopkins, Ramona O.; Squire, Larry R.

    2014-01-01

    Hippocampal damage has been thought to result in broad memory impairment. Recent studies in humans, however, have raised the possibility that recognition memory for faces might be spared. In five experiments we investigated face recognition in patients with hippocampal lesions (H) or large medial temporal lobe (MTL) lesions, including patients where neurohistological information was available. Recognition of novel faces was unequivocally intact in H patients but only at a short retention interval. Recognition memory for words, buildings, inverted faces, and famous faces was impaired. For MTL patients, recognition memory was impaired for all materials and across all retention intervals. These results indicate that structures other than the hippocampus, perhaps the perirhinal cortex, can support face recognition memory in H patients under some conditions. The fact that the faces were novel when recognition memory was intact does not fully account for our findings. We propose that the role of the hippocampus in recognition memory is related to how recognition decisions are accomplished. In typical recognition tasks, participants proceed by forming an association between a study item and the study list, and the recognition decision is later made based on whether participants believe the item was on the study list. We suggest that face recognition is an exception to this principle and that, at short retention intervals, participants can make their recognition decisions without making explicit reference to the study list. Important features of faces that might make face recognition exceptional are that they are processed holistically and are difficult to verbally label. PMID:24958865

  8. Character Recognition Using Genetically Trained Neural Networks

    SciTech Connect

    Diniz, C.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-10-01

    Computationally intelligent recognition of characters and symbols addresses a wide range of applications including foreign language translation and chemical formula identification. The combination of intelligent learning and optimization algorithms with layered neural structures offers powerful techniques for character recognition. These techniques were originally developed by Sandia National Laboratories for pattern and spectral analysis; however, their ability to optimize vast amounts of data make them ideal for character recognition. An adaptation of the Neural Network Designer soflsvare allows the user to create a neural network (NN_) trained by a genetic algorithm (GA) that correctly identifies multiple distinct characters. The initial successfid recognition of standard capital letters can be expanded to include chemical and mathematical symbols and alphabets of foreign languages, especially Arabic and Chinese. The FIN model constructed for this project uses a three layer feed-forward architecture. To facilitate the input of characters and symbols, a graphic user interface (GUI) has been developed to convert the traditional representation of each character or symbol to a bitmap. The 8 x 8 bitmap representations used for these tests are mapped onto the input nodes of the feed-forward neural network (FFNN) in a one-to-one correspondence. The input nodes feed forward into a hidden layer, and the hidden layer feeds into five output nodes correlated to possible character outcomes. During the training period the GA optimizes the weights of the NN until it can successfully recognize distinct characters. Systematic deviations from the base design test the network's range of applicability. Increasing capacity, the number of letters to be recognized, requires a nonlinear increase in the number of hidden layer neurodes. Optimal character recognition performance necessitates a minimum threshold for the number of cases when genetically training the net. And, the amount of

  9. Toward understanding the limits of gait recognition

    NASA Astrophysics Data System (ADS)

    Liu, Zongyi; Malave, Laura; Osuntogun, Adebola; Sudhakar, Preksha; Sarkar, Sudeep

    2004-08-01

    Most state of the art video-based gait recognition algorithms start from binary silhouettes. These silhouettes, defined as foreground regions, are usually detected by background subtraction methods, which results in holes or missed parts due to similarity of foreground and background color, and boundary errors due to video compression artifacts. Errors in low-level representation make it hard to understand the effect of certain conditions, such as surface and time, on gait recognition. In this paper, we present a part-level, manual silhouette database consisting of 71 subjects, over one gait cycle, with differences in surface, shoe-type, carrying condition, and time. We have a total of about 11,000 manual silhouette frames. The purpose of this manual silhouette database is twofold. First, this is a resource that we make available at http://www.GaitChallenge.org for use by the gait community to test and design better silhouette detection algorithms. These silhouettes can also be used to learn gait dynamics. Second, using the baseline gait recognition algorithm, which was specified along with the HumanID Gait Challenge problem, we show that performance from manual silhouettes is similar and only sometimes better than that from automated silhouettes detected by statistical background subtraction. Low performances when comparing sequences with differences in walking surfaces and time-variation are not fully explained by silhouette quality. We also study the recognition power in each body part and show that recognition based on just the legs is equal to that from the whole silhouette. There is also significant recognition power in the head and torso shape.

  10. Recognition methods for 3D textured surfaces

    NASA Astrophysics Data System (ADS)

    Cula, Oana G.; Dana, Kristin J.

    2001-06-01

    Texture as a surface representation is the subject of a wide body of computer vision and computer graphics literature. While texture is always associated with a form of repetition in the image, the repeating quantity may vary. The texture may be a color or albedo variation as in a checkerboard, a paisley print or zebra stripes. Very often in real-world scenes, texture is instead due to a surface height variation, e.g. pebbles, gravel, foliage and any rough surface. Such surfaces are referred to here as 3D textured surfaces. Standard texture recognition algorithms are not appropriate for 3D textured surfaces because the appearance of these surfaces changes in a complex manner with viewing direction and illumination direction. Recent methods have been developed for recognition of 3D textured surfaces using a database of surfaces observed under varied imaging parameters. One of these methods is based on 3D textons obtained using K-means clustering of multiscale feature vectors. Another method uses eigen-analysis originally developed for appearance-based object recognition. In this work we develop a hybrid approach that employs both feature grouping and dimensionality reduction. The method is tested using the Columbia-Utrecht texture database and provides excellent recognition rates. The method is compared with existing recognition methods for 3D textured surfaces. A direct comparison is facilitated by empirical recognition rates from the same texture data set. The current method has key advantages over existing methods including requiring less prior information on both the training and novel images.

  11. Human action recognition using integrated model

    NASA Astrophysics Data System (ADS)

    Yi, Yang; Lin, Yikun

    2013-07-01

    A novel action recognition framework based on integrated model is proposed in the paper. First, the covariance descriptor is utilized to extract features from video sequences, and then each class specific codebook is constructed and appended to the global codebook. A static model applying the template matching technique and a dynamic model employing the trigram model are learned to capture complementary information in an action. And lastly, an integrated model is used to estimate the confidence of the static and dynamic models and produces a reliable result. Comparative experiments show that our presented method achieves superior results over other state-of-the-art approaches. Keywords: human action recognition, covariance descriptor, integrated model

  12. Pattern Recognition via PCNN and Tsallis Entropy

    PubMed Central

    Zhang, YuDong; Wu, LeNan

    2008-01-01

    In this paper a novel feature extraction method for image processing via PCNN and Tsallis entropy is presented. We describe the mathematical model of the PCNN and the basic concept of Tsallis entropy in order to find a recognition method for isolated objects. Experiments show that the novel feature is translation and scale independent, while rotation independence is a bit weak at diagonal angles of 45° and 135°. Parameters of the application on face recognition are acquired by bacterial chemotaxis optimization (BCO), and the highest classification rate is 72.5%, which demonstrates its acceptable performance and potential value.

  13. Convolution neural networks for ship type recognition

    NASA Astrophysics Data System (ADS)

    Rainey, Katie; Reeder, John D.; Corelli, Alexander G.

    2016-05-01

    Algorithms to automatically recognize ship type from satellite imagery are desired for numerous maritime applications. This task is difficult, and example imagery accurately labeled with ship type is hard to obtain. Convolutional neural networks (CNNs) have shown promise in image recognition settings, but many of these applications rely on the availability of thousands of example images for training. This work attempts to under- stand for which types of ship recognition tasks CNNs might be well suited. We report the results of baseline experiments applying a CNN to several ship type classification tasks, and discuss many of the considerations that must be made in approaching this problem.

  14. Exploring Biomolecular Recognition by Modeling and Simulation

    NASA Astrophysics Data System (ADS)

    Wade, Rebecca

    2007-12-01

    Biomolecular recognition is complex. The balance between the different molecular properties that contribute to molecular recognition, such as shape, electrostatics, dynamics and entropy, varies from case to case. This, along with the extent of experimental characterization, influences the choice of appropriate computational approaches to study biomolecular interactions. I will present computational studies in which we aim to make concerted use of bioinformatics, biochemical network modeling and molecular simulation techniques to study protein-protein and protein-small molecule interactions and to facilitate computer-aided drug design.

  15. Stereo vision with distance and gradient recognition

    NASA Astrophysics Data System (ADS)

    Kim, Soo-Hyun; Kang, Suk-Bum; Yang, Tae-Kyu

    2007-12-01

    Robot vision technology is needed for the stable walking, object recognition and the movement to the target spot. By some sensors which use infrared rays and ultrasonic, robot can overcome the urgent state or dangerous time. But stereo vision of three dimensional space would make robot have powerful artificial intelligence. In this paper we consider about the stereo vision for stable and correct movement of a biped robot. When a robot confront with an inclination plane or steps, particular algorithms are needed to go on without failure. This study developed the recognition algorithm of distance and gradient of environment by stereo matching process.

  16. Gait recognition based on fusion features

    NASA Astrophysics Data System (ADS)

    Wu, Haizhen; Jiang, Jiafu; Chen, Xi

    2009-10-01

    Gait recognition and analysis is a promising biometrics technology finding applications in numerous sectors of our society. This paper proposes a new fusion algorithm where the static and dynamic features are fused to obtain optimal performance. The new fusion algorithm divides decision situations into two categories. The wavelet moment is used to describe the static features of gait sequence images, and the three widths of the body contour are used to describe the dynamic features. In addition, the Principal Component Analysis (PCA) for feature transformation of spatial templates is proposed. The experimental results demonstrate that the proposed algorithm performs an encouraging recognition rate.

  17. Recognition of dementia in hospitalized older adults.

    PubMed

    Maslow, Katie; Mezey, Mathy

    2008-01-01

    Many hospital patients with dementia have no documented dementia diagnosis. In some cases, this is because they have never been diagnosed. Recognition of Dementia in Hospitalized Older Adults proposes several approaches that hospital nurses can use to increase recognition of dementia. This article describes the Try This approaches, how to implement them, and how to incorporate them into a hospital's current admission procedures. For a free online video demonstrating the use of these approaches, go to http://links.lww.com/A216. PMID:18156858

  18. Fungal glycans and the innate immune recognition

    PubMed Central

    Barreto-Bergter, Eliana; Figueiredo, Rodrigo T.

    2014-01-01

    Polysaccharides such as α- and β-glucans, chitin, and glycoproteins extensively modified with both N- and O-linked carbohydrates are the major components of fungal surfaces. The fungal cell wall is an excellent target for the action of antifungal agents, since most of its components are absent from mammalian cells. Recognition of these carbohydrate-containing molecules by the innate immune system triggers inflammatory responses and activation of microbicidal mechanisms by leukocytes. This review will discuss the structure of surface fungal glycoconjugates and polysaccharides and their recognition by innate immune receptors. PMID:25353009

  19. Correlation, functional analysis and optical pattern recognition

    SciTech Connect

    Dickey, F.M.; Lee, M.L.; Stalker, K.T.

    1994-03-01

    Correlation integrals have played a central role in optical pattern recognition. The success of correlation, however, has been limited. What is needed is a mathematical operation more complex than correlation. Suitably complex operations are the functionals defined on the Hilbert space of Lebesgue square integrable functions. Correlation is a linear functional of a parameter. In this paper, we develop a representation of functionals in terms of inner products or equivalently correlation functions. We also discuss the role of functionals in neutral networks. Having established a broad relation of correlation to pattern recognition, we discuss the computation of correlation functions using acousto-optics.

  20. Phonematic recognition by linear prediction: Experiment

    NASA Astrophysics Data System (ADS)

    Miclet, L.; Grenier, Y.; Leroux, J.

    The recognition of speech signals analyzed by linear prediction is introduced. The principle of the channel adapted vocoder (CAV) is outlined. The learning of each channel model and adaptation to the speaker are discussed. A method stemming from the canonical analysis of correlations is given. This allows, starting with the CAV of one speaker, the calculation of that of another. The projection function is learned from a series of key words pronounced by both speakers. The reconstruction of phonemes can be explained by recognition factors arising from the vocoder. Automata associated with the channels are used for local smoothing and series of segments are treated in order to produce a phonemic lattice.

  1. Incorporating Duration Information in Activity Recognition

    NASA Astrophysics Data System (ADS)

    Chaurasia, Priyanka; Scotney, Bryan; McClean, Sally; Zhang, Shuai; Nugent, Chris

    Activity recognition has become a key issue in smart home environments. The problem involves learning high level activities from low level sensor data. Activity recognition can depend on several variables; one such variable is duration of engagement with sensorised items or duration of intervals between sensor activations that can provide useful information about personal behaviour. In this paper a probabilistic learning algorithm is proposed that incorporates episode, time and duration information to determine inhabitant identity and the activity being undertaken from low level sensor data. Our results verify that incorporating duration information consistently improves the accuracy.

  2. Face recognition motivated by human approach

    NASA Astrophysics Data System (ADS)

    Kamgar-Parsi, Behrooz; Lawson, Wallace Edgar; Kamgar-Parsi, Behzad

    2010-04-01

    We report the development of a face recognition system which operates in the same way as humans in that it is capable of recognizing a number of people, while rejecting everybody else as strangers. While humans do it routinely, a particularly challenging aspect of the problem of open-world face recognition has been the question of rejecting previously unseen faces as unfamiliar. Our approach can handle previously unseen faces; it is based on identifying and enclosing the region(s) in the human face space which belong to the target person(s).

  3. A Synchronization Account of False Recognition

    ERIC Educational Resources Information Center

    Johns, Brendan T.; Jones, Michael N.; Mewhort, Douglas J. K.

    2012-01-01

    We describe a computational model to explain a variety of results in both standard and false recognition. A key attribute of the model is that it uses plausible semantic representations for words, built through exposure to a linguistic corpus. A study list is encoded in the model as a gist trace, similar to the proposal of fuzzy trace theory…

  4. ORNL Biometric Eye Model for Iris Recognition

    SciTech Connect

    Santos-Villalobos, Hector J; Barstow, Del R; Karakaya, Mahmut; Chaum, Edward; Boehnen, Chris Bensing

    2012-01-01

    Iris recognition has been proven to be an accurate and reliable biometric. However, the recognition of non-ideal iris images such as off angle images is still an unsolved problem. We propose a new biometric targeted eye model and a method to reconstruct the off-axis eye to its frontal view allowing for recognition using existing methods and algorithms. This allows for existing enterprise level algorithms and approaches to be largely unmodified by using our work as a pre-processor to improve performance. In addition, we describe the `Limbus effect' and its importance for an accurate segmentation of off-axis irides. Our method uses an anatomically accurate human eye model and ray-tracing techniques to compute a transformation function, which reconstructs the iris to its frontal, non-refracted state. Then, the same eye model is used to render a frontal view of the reconstructed iris. The proposed method is fully described and results from synthetic data are shown to establish an upper limit on performance improvement and establish the importance of the proposed approach over traditional linear elliptical unwrapping methods. Our results with synthetic data demonstrate the ability to perform an accurate iris recognition with an image taken as much as 70 degrees off-axis.

  5. Partial face recognition: alignment-free approach.

    PubMed

    Liao, Shengcai; Jain, Anil K; Li, Stan Z

    2013-05-01

    Numerous methods have been developed for holistic face recognition with impressive performance. However, few studies have tackled how to recognize an arbitrary patch of a face image. Partial faces frequently appear in unconstrained scenarios, with images captured by surveillance cameras or handheld devices (e.g., mobile phones) in particular. In this paper, we propose a general partial face recognition approach that does not require face alignment by eye coordinates or any other fiducial points. We develop an alignment-free face representation method based on Multi-Keypoint Descriptors (MKD), where the descriptor size of a face is determined by the actual content of the image. In this way, any probe face image, holistic or partial, can be sparsely represented by a large dictionary of gallery descriptors. A new keypoint descriptor called Gabor Ternary Pattern (GTP) is also developed for robust and discriminative face recognition. Experimental results are reported on four public domain face databases (FRGCv2.0, AR, LFW, and PubFig) under both the open-set identification and verification scenarios. Comparisons with two leading commercial face recognition SDKs (PittPatt and FaceVACS) and two baseline algorithms (PCA+LDA and LBP) show that the proposed method, overall, is superior in recognizing both holistic and partial faces without requiring alignment. PMID:23520259

  6. Recognition of Prior Vocational Learning in Sweden

    ERIC Educational Resources Information Center

    Andersson, Per; Fejes, Andreas; Ahn, Song-Ee

    2004-01-01

    Initiatives in the recognition of prior learning (RPL) have been taken in Sweden in recent years, mainly focusing on prior vocational learning among immigrants. The government started different projects to find methods for recognising a person's prior learning in the field of vocational competence. This article presents a study of how these…

  7. Automatic target recognition via sparse representations

    NASA Astrophysics Data System (ADS)

    Estabridis, Katia

    2010-04-01

    Automatic target recognition (ATR) based on the emerging technology of Compressed Sensing (CS) can considerably improve accuracy, speed and cost associated with these types of systems. An image based ATR algorithm has been built upon this new theory, which can perform target detection and recognition in a low dimensional space. Compressed dictionaries (A) are formed to include rotational information for a scale of interest. The algorithm seeks to identify y(test sample) as a linear combination of the dictionary elements : y=Ax, where A ∈ Rnxm(n<recognition problems are solved by finding the sparse-solution to the undetermined system y=Ax via Orthogonal Matching Pursuit (OMP) and l1 minimization techniques. Visible and MWIR imagery collected by the Army Night Vision and Electronic Sensors Directorate (NVESD) was utilized to test the algorithm. Results show an average detection and recognition rates above 95% for targets at ranges up to 3Km for both image modalities.

  8. Risk Recognition and Intimate Partner Violence

    ERIC Educational Resources Information Center

    Witte, Tricia H.; Kendra, Rachel

    2010-01-01

    The objective of this study was to determine whether female victims of physical forms of intimate partner violence (IPV) displayed deficits in risk recognition, or the ability to detect danger, in physically violent dating encounters. A total of 182 women watched a video depicting a psychologically and physically aggressive encounter between…

  9. Contextual Constraints on Ambiguous Word Recognition.

    ERIC Educational Resources Information Center

    Schvaneveldt, Roger W.; And Others

    Two major hypotheses are currently at issue concerning the effects of semantic context on ambiguous word recognition: (1) the selective-retrieval hypothesis (SRH) maintains that a single meaning is retrieved from memory, and (2) the nonselective-retrieval hypothesis maintains that all meanings are retrieved from memory. To help clear up this…

  10. Face Recognition: Canonical Mechanisms at Multiple Timescales.

    PubMed

    Giese, Martin A

    2016-07-11

    Adaptation is ubiquitous in the nervous system, and many possible computational roles have been discussed. A new functional imaging study suggests that, in face recognition, the learning of 'norm faces' and adaptation resulting in perceptual after-effects depend on the same mechanism. PMID:27404241

  11. Facial expression recognition in perceptual color space.

    PubMed

    Lajevardi, Seyed Mehdi; Wu, Hong Ren

    2012-08-01

    This paper introduces a tensor perceptual color framework (TPCF) for facial expression recognition (FER), which is based on information contained in color facial images. The TPCF enables multi-linear image analysis in different color spaces and demonstrates that color components provide additional information for robust FER. Using this framework, the components (in either RGB, YCbCr, CIELab or CIELuv space) of color images are unfolded to two-dimensional (2- D) tensors based on multi-linear algebra and tensor concepts, from which the features are extracted by Log-Gabor filters. The mutual information quotient (MIQ) method is employed for feature selection. These features are classified using a multi-class linear discriminant analysis (LDA) classifier. The effectiveness of color information on FER using low-resolution and facial expression images with illumination variations is assessed for performance evaluation. Experimental results demonstrate that color information has significant potential to improve emotion recognition performance due to the complementary characteristics of image textures. Furthermore, the perceptual color spaces (CIELab and CIELuv) are better overall for facial expression recognition than other color spaces by providing more efficient and robust performance for facial expression recognition using facial images with illumination variation. PMID:22575677

  12. Size Scaling in Visual Pattern Recognition

    ERIC Educational Resources Information Center

    Larsen, Axel; Bundesen, Claus

    1978-01-01

    Human visual recognition on the basis of shape but regardless of size was investigated by reaction time methods. Results suggested two processes of size scaling: mental-image transformation and perceptual-scale transformation. Image transformation accounted for matching performance based on visual short-term memory, whereas scale transformation…

  13. Sex Stereotype Effects in Children's Picture Recognition.

    ERIC Educational Resources Information Center

    Cann, Arnie; Newbern, Sara R.

    1984-01-01

    Reports an experiment in which 80 male and female six and eight year olds were presented with pictures consistent or inconsistent with sex stereotypes and pictures of neutral activities. Later, subjects performed a picture-recognition task. Among the variables investigated were subjects' labeling of pictures and sex-stereotype consistency. (CB)

  14. Recognition of Unfamiliar Talking Faces at Birth

    ERIC Educational Resources Information Center

    Coulon, Marion; Guellai, Bahia; Streri, Arlette

    2011-01-01

    Sai (2005) investigated the role of speech in newborns' recognition of their mothers' faces. Her results revealed that, when presented with both their mother's face and that of a stranger, newborns preferred looking at their mother only if she had previously talked to them. The present study attempted to extend these findings to any other faces.…

  15. Automatic TLI recognition system beta prototype testing

    SciTech Connect

    Lassahn, G.D.

    1996-06-01

    This report describes the beta prototype automatic target recognition system ATR3, and some performance tests done with this system. This is a fully operational system, with a high computational speed. It is useful for findings any kind of target in digitized image data, and as a general purpose image analysis tool.

  16. Pattern recognition receptors in antifungal immunity.

    PubMed

    Plato, Anthony; Hardison, Sarah E; Brown, Gordon D

    2015-03-01

    Receptors of the innate immune system are the first line of defence against infection, being able to recognise and initiate an inflammatory response to invading microorganisms. The Toll-like (TLR), NOD-like (NLR), RIG-I-like (RLR) and C-type lectin-like receptors (CLR) are four receptor families that contribute to the recognition of a vast range of species, including fungi. Many of these pattern recognition receptors (PRRs) are able to initiate innate immunity and polarise adaptive responses upon the recognition of fungal cell wall components and other conserved molecular patterns, including fungal nucleic acids. These receptors induce effective mechanisms of fungal clearance in normal hosts, but medical interventions, immunosuppression or genetic predisposition can lead to susceptibility to fungal infections. In this review, we highlight the importance of PRRs in fungal infection, specifically CLRs, which are the major PRR involved. We will describe specific PRRs in detail, the importance of receptor collaboration in fungal recognition and clearance, and describe how genetic aberrations in PRRs can contribute to disease pathology. PMID:25420452

  17. Transfer learning for bimodal biometrics recognition

    NASA Astrophysics Data System (ADS)

    Dan, Zhiping; Sun, Shuifa; Chen, Yanfei; Gan, Haitao

    2013-10-01

    Biometrics recognition aims to identify and predict new personal identities based on their existing knowledge. As the use of multiple biometric traits of the individual may enables more information to be used for recognition, it has been proved that multi-biometrics can produce higher accuracy than single biometrics. However, a common problem with traditional machine learning is that the training and test data should be in the same feature space, and have the same underlying distribution. If the distributions and features are different between training and future data, the model performance often drops. In this paper, we propose a transfer learning method for face recognition on bimodal biometrics. The training and test samples of bimodal biometric images are composed of the visible light face images and the infrared face images. Our algorithm transfers the knowledge across feature spaces, relaxing the assumption of same feature space as well as same underlying distribution by automatically learning a mapping between two different but somewhat similar face images. According to the experiments in the face images, the results show that the accuracy of face recognition has been greatly improved by the proposed method compared with the other previous methods. It demonstrates the effectiveness and robustness of our method.

  18. Multiple degree of freedom optical pattern recognition

    NASA Technical Reports Server (NTRS)

    Casasent, D.

    1987-01-01

    Three general optical approaches to multiple degree of freedom object pattern recognition (where no stable object rest position exists) are advanced. These techniques include: feature extraction, correlation, and artificial intelligence. The details of the various processors are advanced together with initial results.

  19. Test Sequence Priming in Recognition Memory

    ERIC Educational Resources Information Center

    Johns, Elizabeth E.; Mewhort, D. J. K.

    2009-01-01

    The authors examined priming within the test sequence in 3 recognition memory experiments. A probe primed its successor whenever both probes shared a feature with the same studied item ("interjacent priming"), indicating that the study item like the probe is central to the decision. Interjacent priming occurred even when the 2 probes did not…

  20. Automatic speech recognition in air traffic control

    NASA Technical Reports Server (NTRS)

    Karlsson, Joakim

    1990-01-01

    Automatic Speech Recognition (ASR) technology and its application to the Air Traffic Control system are described. The advantages of applying ASR to Air Traffic Control, as well as criteria for choosing a suitable ASR system are presented. Results from previous research and directions for future work at the Flight Transportation Laboratory are outlined.

  1. Face Recognition Increases during Saccade Preparation

    PubMed Central

    Lin, Hai; Rizak, Joshua D.; Ma, Yuan-ye; Yang, Shang-chuan; Chen, Lin; Hu, Xin-tian

    2014-01-01

    Face perception is integral to human perception system as it underlies social interactions. Saccadic eye movements are frequently made to bring interesting visual information, such as faces, onto the fovea for detailed processing. Just before eye movement onset, the processing of some basic features, such as the orientation, of an object improves at the saccade landing point. Interestingly, there is also evidence that indicates faces are processed in early visual processing stages similar to basic features. However, it is not known whether this early enhancement of processing includes face recognition. In this study, three experiments were performed to map the timing of face presentation to the beginning of the eye movement in order to evaluate pre-saccadic face recognition. Faces were found to be similarly processed as simple objects immediately prior to saccadic movements. Starting ∼ 120 ms before a saccade to a target face, independent of whether or not the face was surrounded by other faces, the face recognition gradually improved and the critical spacing of the crowding decreased as saccade onset was approaching. These results suggest that an upcoming saccade prepares the visual system for new information about faces at the saccade landing site and may reduce the background in a crowd to target the intended face. This indicates an important role of pre-saccadic eye movement signals in human face recognition. PMID:24671174

  2. Guideline for Optical Character Recognition Forms.

    ERIC Educational Resources Information Center

    National Bureau of Standards (DOC), Washington, DC.

    This publication provides materials relating to the design, preparation, acquisition, inspection, and application of Optical Character Recognition (OCR) forms in data entry systems. Since the materials are advisory and tutorial in nature, this publication has been issued as a guideline rather than as a standard in the Federal Information…

  3. Molecular recognition: The I's have it

    NASA Astrophysics Data System (ADS)

    Taylor, Mark S.

    2014-12-01

    Rotaxanes with cyclodextrin end groups have been used as a platform to investigate anion binding in water, revealing that halogen bonding can serve as the basis for molecular recognition in aqueous solvents, which may have implications in medicinal chemistry and beyond.

  4. Word Spotting and Recognition with Embedded Attributes.

    PubMed

    Almazán, Jon; Gordo, Albert; Fornés, Alicia; Valveny, Ernest

    2014-12-01

    This paper addresses the problems of word spotting and word recognition on images. In word spotting, the goal is to find all instances of a query word in a dataset of images. In recognition, the goal is to recognize the content of the word image, usually aided by a dictionary or lexicon. We describe an approach in which both word images and text strings are embedded in a common vectorial subspace. This is achieved by a combination of label embedding and attributes learning, and a common subspace regression. In this subspace, images and strings that represent the same word are close together, allowing one to cast recognition and retrieval tasks as a nearest neighbor problem. Contrary to most other existing methods, our representation has a fixed length, is low dimensional, and is very fast to compute and, especially, to compare. We test our approach on four public datasets of both handwritten documents and natural images showing results comparable or better than the state-of-the-art on spotting and recognition tasks. PMID:26353157

  5. Recognition system rapid application prototyping tool

    NASA Astrophysics Data System (ADS)

    Mills, Stuart A.; Karins, James P.; Dydyk, Robert B.

    1997-03-01

    The recognition system rapid application prototyping tool (RSRAPT) was developed to evaluate various potential configurations of miniature ruggedized optical correlator (MROC) modules and to rapidly assess the feasibility of their use within systems such as missile seekers. RSRAPT is a simulation environment for rapidly prototyping, developing, and evaluating recognition systems that incorporate MROC technology. It is designed to interface to OLE compliant Windows applications using standard OLE interfaces. The system consists of nine key functional elements: sensor, detection, segmentation, pre-processor, filter selection, correlator, post-processor, identifier, and controller. The RSRAPT is a collection of object oriented server components, a client user interface and a recognitions system image and image sensor database. The server components are implemented to encapsulate processes that are typical to any optical-correlator based pattern recognition system. All the servers are implemented as Microsoft component object model objects. In addition to the system servers there are two key 'helper servers.' The first is the image server, which encapsulates all 'images'. This includes gray scale images and even complex images. The other supporting server is the filter generation server. This server trains the system on user data by calculating filters for user selected image types. The system hosts a library of standard image processing routines such as convolution, edge operators, clustering algorithms, median filtering, morphological operators such as erosion and dilation, connected components, region growing, and adaptive thresholding. In this paper we describe the simulator and show sample results from diverse applications.

  6. Psychological and Associative Meaning in Auditory Recognition.

    ERIC Educational Resources Information Center

    Tarte, Robert; And Others

    In 1964 Tarte, Gadlin, and Ehrlich found a correlation between Galvanic Skin Response (GSR) and associative meaning in an auditory recognition task. This study attempted to replicate the results and examine the critical variables involved. One hundred eighty female college students served as subjects. Each heard ten accelerated words followed by…

  7. Cockpit voice recognition program at Princeton University

    NASA Technical Reports Server (NTRS)

    Huang, C. Y.

    1983-01-01

    Voice recognition technology (VRT) is applied to aeronautics, particularly on the pilot workload alleviation. The VRT does not have to prove its maturity any longer. The feasibility of voice tuning of radio and DME are demonstrated since there are immediate advantages to the pilot and can be completed in a reasonable time.

  8. Item Effects in Recognition Memory for Words

    ERIC Educational Resources Information Center

    Freeman, Emily; Heathcote, Andrew; Chalmers, Kerry; Hockley, William

    2010-01-01

    We investigate the effects of word characteristics on episodic recognition memory using analyses that avoid Clark's (1973) "language-as-a-fixed-effect" fallacy. Our results demonstrate the importance of modeling word variability and show that episodic memory for words is strongly affected by item noise (Criss & Shiffrin, 2004), as measured by the…

  9. Conformal Predictions in Multimedia Pattern Recognition

    ERIC Educational Resources Information Center

    Nallure Balasubramanian, Vineeth

    2010-01-01

    The fields of pattern recognition and machine learning are on a fundamental quest to design systems that can learn the way humans do. One important aspect of human intelligence that has so far not been given sufficient attention is the capability of humans to express when they are certain about a decision, or when they are not. Machine learning…

  10. Bilingual Word Recognition in English and Greek.

    ERIC Educational Resources Information Center

    Chitiri, Helena-Fivi; Willows, Dale M.

    1997-01-01

    A study investigated word recognition processes of Greek/English bilinguals in relation to linguistic and syntactic differences in the languages, then compared those processes with those of monolinguals. Bilingual readers performed differently in the languages, conforming more to monolingual patterns in their native language (Greek), interpreted…

  11. Toleration and Recognition: What Should We Teach?

    ERIC Educational Resources Information Center

    Jones, Peter Nigel

    2010-01-01

    Generally we think it good to tolerate and to accord recognition. Yet both are complex phenomena and our teaching must acknowledge and cope with that complexity. We tolerate only what we object to, so our message to students cannot be simply, "promote the good and prevent the bad". Much advocacy of toleration is not what it pretends to be. Nor is…

  12. Local Pyramidal Descriptors for Image Recognition.

    PubMed

    Seidenari, Lorenzo; Serra, Giuseppe; Bagdanov, Andrew D; Del Bimbo, Alberto

    2014-05-01

    In this paper, we present a novel method to improve the flexibility of descriptor matching for image recognition by using local multiresolution pyramids in feature space. We propose that image patches be represented at multiple levels of descriptor detail and that these levels be defined in terms of local spatial pooling resolution. Preserving multiple levels of detail in local descriptors is a way of hedging one's bets on which levels will most relevant for matching during learning and recognition. We introduce the Pyramid SIFT (P-SIFT) descriptor and show that its use in four state-of-the-art image recognition pipelines improves accuracy and yields state-of-the-art results. Our technique is applicable independently of spatial pyramid matching and we show that spatial pyramids can be combined with local pyramids to obtain further improvement. We achieve state-of-the-art results on Caltech-101 (80.1%) and Caltech-256 (52.6%) when compared to other approaches based on SIFT features over intensity images. Our technique is efficient and is extremely easy to integrate into image recognition pipelines. PMID:26353235

  13. Local Pyramidal Descriptors for Image Recognition.

    PubMed

    Seidenari, Lorenzo; Serra, Giuseppe; Bagdanov, Andrew D; Del Bimbo, Alberto

    2013-11-22

    In this paper we present a novel method to improve the flexibility of descriptor matching for image recognition by using local multiresolution pyramids in feature space. We propose that image patches be represented at multiple levels of descriptor detail and that these levels be defined in terms of local spatial pooling resolution. Preserving multiple levels of detail in local descriptors is a way of hedging one's bets on which levels will most relevant for matching during learning and recognition. We introduce the Pyramid SIFT (P-SIFT) descriptor and show that its use in four state-of-the-art image recognition pipelines improves accuracy and yields state-of-the-art results. Our technique is applicable independently of spatial pyramid matching and we show that spatial pyramids can be combined with local pyramids to obtain further improvement. We achieve state-of-the-art results on Caltech-101 (80.1%) and Caltech-256 (52.6%) when compared to other approaches based on SIFT features over intensity images. Our technique is efficient and is extremely easy to integrate into image recognition pipelines. PMID:24277944

  14. Multiculturalism: Examining the Politics of Recognition.

    ERIC Educational Resources Information Center

    Taylor, Charles; And Others

    This volume focuses on the challenge of multiculturalism and the politics of recognition facing democratic societies today, concentrating on the United States and Canada in particular. The initial inquiry by Charles Taylor considers whether the institutions of liberal democratic government make room for, or even should accommodate, recognizing the…

  15. Speech Recognition for A Digital Video Library.

    ERIC Educational Resources Information Center

    Witbrock, Michael J.; Hauptmann, Alexander G.

    1998-01-01

    Production of the meta-data supporting the Informedia Digital Video Library interface is automated using techniques derived from artificial intelligence research. Speech recognition and natural-language processing, information retrieval, and image analysis are applied to produce an interface that helps users locate information and navigate more…

  16. Recognition of Social Identity in Ants

    PubMed Central

    Bos, Nick; d’Ettorre, Patrizia

    2012-01-01

    Recognizing the identity of others, from the individual to the group level, is a hallmark of society. Ants, and other social insects, have evolved advanced societies characterized by efficient social recognition systems. Colony identity is mediated by colony specific signature mixtures, a blend of hydrocarbons present on the cuticle of every individual (the “label”). Recognition occurs when an ant encounters another individual, and compares the label it perceives to an internal representation of its own colony odor (the “template”). A mismatch between label and template leads to rejection of the encountered individual. Although advances have been made in our understanding of how the label is produced and acquired, contradictory evidence exists about information processing of recognition cues. Here, we review the literature on template acquisition in ants and address how and when the template is formed, where in the nervous system it is localized, and the possible role of learning. We combine seemingly contradictory evidence in to a novel, parsimonious theory for the information processing of nestmate recognition cues. PMID:22461777

  17. Iris Recognition: The Consequences of Image Compression

    NASA Astrophysics Data System (ADS)

    Ives, Robert W.; Bishop, Daniel A.; Du, Yingzi; Belcher, Craig

    2010-12-01

    Iris recognition for human identification is one of the most accurate biometrics, and its employment is expanding globally. The use of portable iris systems, particularly in law enforcement applications, is growing. In many of these applications, the portable device may be required to transmit an iris image or template over a narrow-bandwidth communication channel. Typically, a full resolution image (e.g., VGA) is desired to ensure sufficient pixels across the iris to be confident of accurate recognition results. To minimize the time to transmit a large amount of data over a narrow-bandwidth communication channel, image compression can be used to reduce the file size of the iris image. In other applications, such as the Registered Traveler program, an entire iris image is stored on a smart card, but only 4 kB is allowed for the iris image. For this type of application, image compression is also the solution. This paper investigates the effects of image compression on recognition system performance using a commercial version of the Daugman iris2pi algorithm along with JPEG-2000 compression, and links these to image quality. Using the ICE 2005 iris database, we find that even in the face of significant compression, recognition performance is minimally affected.

  18. Word recognition using ideal word patterns

    NASA Astrophysics Data System (ADS)

    Zhao, Sheila X.; Srihari, Sargur N.

    1994-03-01

    The word shape analysis approach to text recognition is motivated by discoveries in psychological studies of the human reading process. It attempts to describe and compare the shape of the word as a whole object without trying to segment and recognize the individual characters, so it bypasses the errors committed in character segmentation and classification. However, the large number of classes and large variation and distortion expected in all patterns belonging to the same class make it difficult for conventional, accurate, pattern recognition approaches. A word shape analysis approach using ideal word patterns to overcome the difficulty and improve recognition performance is described in this paper. A special word pattern which characterizes a word class is extracted from different sample patterns of the word class and stored in memory. Recognition of a new word pattern is achieved by comparing it with the special pattern of each word class called ideal word pattern. The process of generating the ideal word pattern of each word class is proposed. The algorithm was tested on a set of machine printed gray scale word images which included a wide range of print types and qualities.

  19. Face photo-sketch synthesis and recognition.

    PubMed

    Wang, Xiaogang; Tang, Xiaoou

    2009-11-01

    In this paper, we propose a novel face photo-sketch synthesis and recognition method using a multiscale Markov Random Fields (MRF) model. Our system has three components: 1) given a face photo, synthesizing a sketch drawing; 2) given a face sketch drawing, synthesizing a photo; and 3) searching for face photos in the database based on a query sketch drawn by an artist. It has useful applications for both digital entertainment and law enforcement. We assume that faces to be studied are in a frontal pose, with normal lighting and neutral expression, and have no occlusions. To synthesize sketch/photo images, the face region is divided into overlapping patches for learning. The size of the patches decides the scale of local face structures to be learned. From a training set which contains photo-sketch pairs, the joint photo-sketch model is learned at multiple scales using a multiscale MRF model. By transforming a face photo to a sketch (or transforming a sketch to a photo), the difference between photos and sketches is significantly reduced, thus allowing effective matching between the two in face sketch recognition. After the photo-sketch transformation, in principle, most of the proposed face photo recognition approaches can be applied to face sketch recognition in a straightforward way. Extensive experiments are conducted on a face sketch database including 606 faces, which can be downloaded from our Web site (http://mmlab.ie.cuhk.edu.hk/facesketch.html). PMID:19762924

  20. The Recognition and Reward of Employee Performance.

    ERIC Educational Resources Information Center

    Bishop, John

    A study compared different firms' methods of recognizing and rewarding employee performance and examined the impact of such recognition and reward on such factors as involuntary and voluntary labor turnover and worker productivity. Data from a survey of 3,412 employers that was sponsored by the National Institute of Education and the National…

  1. Pronunciation Modeling for Large Vocabulary Speech Recognition

    ERIC Educational Resources Information Center

    Kantor, Arthur

    2010-01-01

    The large pronunciation variability of words in conversational speech is one of the major causes of low accuracy in automatic speech recognition (ASR). Many pronunciation modeling approaches have been developed to address this problem. Some explicitly manipulate the pronunciation dictionary as well as the set of the units used to define the…

  2. Effects of Cognitive Load on Speech Recognition

    ERIC Educational Resources Information Center

    Mattys, Sven L.; Wiget, Lukas

    2011-01-01

    The effect of cognitive load (CL) on speech recognition has received little attention despite the prevalence of CL in everyday life, e.g., dual-tasking. To assess the effect of CL on the interaction between lexically-mediated and acoustically-mediated processes, we measured the magnitude of the "Ganong effect" (i.e., lexical bias on phoneme…

  3. Music Education Intervention Improves Vocal Emotion Recognition

    ERIC Educational Resources Information Center

    Mualem, Orit; Lavidor, Michal

    2015-01-01

    The current study is an interdisciplinary examination of the interplay among music, language, and emotions. It consisted of two experiments designed to investigate the relationship between musical abilities and vocal emotional recognition. In experiment 1 (N = 24), we compared the influence of two short-term intervention programs--music and…

  4. Kin-informative recognition cues in ants

    PubMed Central

    Nehring, Volker; Evison, Sophie E. F.; Santorelli, Lorenzo A.; d'Ettorre, Patrizia; Hughes, William O. H.

    2011-01-01

    Although social groups are characterized by cooperation, they are also often the scene of conflict. In non-clonal systems, the reproductive interests of group members will differ and individuals may benefit by exploiting the cooperative efforts of other group members. However, such selfish behaviour is thought to be rare in one of the classic examples of cooperation—social insect colonies—because the colony-level costs of individual selfishness select against cues that would allow workers to recognize their closest relatives. In accord with this, previous studies of wasps and ants have found little or no kin information in recognition cues. Here, we test the hypothesis that social insects do not have kin-informative recognition cues by investigating the recognition cues and relatedness of workers from four colonies of the ant Acromyrmex octospinosus. Contrary to the theoretical prediction, we show that the cuticular hydrocarbons of ant workers in all four colonies are informative enough to allow full-sisters to be distinguished from half-sisters with a high accuracy. These results contradict the hypothesis of non-heritable recognition cues and suggest that there is more potential for within-colony conflicts in genetically diverse societies than previously thought. PMID:21123270

  5. Recognition Memory for Male and Female Faces.

    ERIC Educational Resources Information Center

    Yarmey, A. Daniel

    Sex differences in memory for human faces is reviewed. It is found that research evidence to date is not conclusive, but where differences exist they favor female superiority over males in facial memory. In particular, evidence is cited to suggest that females are reliably superior to males in their recognition memory for other females. This is…

  6. Recognition of Hits in a Target

    NASA Astrophysics Data System (ADS)

    Semerak, Vojtech; Drahansky, Martin

    This paper describes two possible ways of hit recognition in a target. First method is based on frame differencing with use of a stabilization algorithm to eliminate movements of a target. Second method uses flood fill with random seed point definition to find hits in the target scene.

  7. Ear recognition from one sample per person.

    PubMed

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods. PMID:26024226

  8. Ear Recognition from One Sample Per Person

    PubMed Central

    Chen, Long; Mu, Zhichun; Zhang, Baoqing; Zhang, Yi

    2015-01-01

    Biometrics has the advantages of efficiency and convenience in identity authentication. As one of the most promising biometric-based methods, ear recognition has received broad attention and research. Previous studies have achieved remarkable performance with multiple samples per person (MSPP) in the gallery. However, most conventional methods are insufficient when there is only one sample per person (OSPP) available in the gallery. To solve the OSPP problem by maximizing the use of a single sample, this paper proposes a hybrid multi-keypoint descriptor sparse representation-based classification (MKD-SRC) ear recognition approach based on 2D and 3D information. Because most 3D sensors capture 3D data accessorizing the corresponding 2D data, it is sensible to use both types of information. First, the ear region is extracted from the profile. Second, keypoints are detected and described for both the 2D texture image and 3D range image. Then, the hybrid MKD-SRC algorithm is used to complete the recognition with only OSPP in the gallery. Experimental results on a benchmark dataset have demonstrated the feasibility and effectiveness of the proposed method in resolving the OSPP problem. A Rank-one recognition rate of 96.4% is achieved for a gallery of 415 subjects, and the time involved in the computation is satisfactory compared to conventional methods. PMID:26024226

  9. Model Professional Development Programs Win Recognition.

    ERIC Educational Resources Information Center

    Price, Kathleen C., Ed.; Quinn, Peggy, Ed.

    1999-01-01

    This bulletin is designed to illustrate the broad range of research and improvement activities supported by the Office of Educational Research and Improvement. Contents include: "Model Professional Development Programs Win Recognition,""Are Our Schools Safe?,""Charter Schools on the Rise,""What to Expect Your First Year of Teaching,""Evaluating…

  10. The Neural Correlates of Everyday Recognition Memory

    ERIC Educational Resources Information Center

    Milton, F.; Muhlert, N.; Butler, C. R.; Benattayallah, A.; Zeman, A. Z.

    2011-01-01

    We used a novel automatic camera, SenseCam, to create a recognition memory test for real-life events. Adapting a "Remember/Know" paradigm, we asked healthy undergraduates, who wore SenseCam for 2 days, in their everyday environments, to classify images as strongly or weakly remembered, strongly or weakly familiar or novel, while brain activation…

  11. Teaching Recognition Skills to Improve Products.

    ERIC Educational Resources Information Center

    Knight, G. William; And Others

    1990-01-01

    First year dental students (n=86) in a conservative restorations course were taught a discrimination learning paradigm to improve production quality. Evaluation of Class 1 amalgam preparations indicates the improved recognition skills corresponded with improved cavity preparation, supporting the use of this teaching model. (Author/MSE)

  12. Plastic Antibodies: Molecular Recognition with Imprinted Polymers

    ERIC Educational Resources Information Center

    Rushton, Gregory T.; Furmanski, Brian; Shimizu, Ken D.

    2005-01-01

    Synthetic polymers are prepared and tested in a study for their molecular recognition properties of an adenine derivative, ethyl adenine-9-acetate (EA9A), within two laboratory periods. The procedure introduces undergraduate chemistry students to noncovalent molecular imprinting as well as the analytical techniques for assessing their recognition…

  13. Speech Recognition Technology for Disabilities Education

    ERIC Educational Resources Information Center

    Tang, K. Wendy; Kamoua, Ridha; Sutan, Victor; Farooq, Omer; Eng, Gilbert; Chu, Wei Chern; Hou, Guofeng

    2005-01-01

    Speech recognition is an alternative to traditional methods of interacting with a computer, such as textual input through a keyboard. An effective system can replace or reduce the reliability on standard keyboard and mouse input. This can especially assist dyslexic students who have problems with character or word use and manipulation in a textual…

  14. Speech Recognition: A World of Opportunities

    ERIC Educational Resources Information Center

    PACER Center, 2004

    2004-01-01

    Speech recognition technology helps people with disabilities interact with computers more easily. People with motor limitations, who cannot use a standard keyboard and mouse, can use their voices to navigate the computer and create documents. The technology is also useful to people with learning disabilities who experience difficulty with spelling…

  15. Speech Recognition, Disability, and College Composition

    ERIC Educational Resources Information Center

    Nelson, Lorna M.; Reynolds, Thomas W., Jr.

    2015-01-01

    This study examined the composing processes of five postsecondary students who used or were learning to use speech recognition software (SR) for college-level writing. The study analyzed their composing processes through observation, interviews, and analysis of written products over a series of composing sessions. This investigation was prompted…

  16. Speech Recognition Thresholds for Multilingual Populations.

    ERIC Educational Resources Information Center

    Ramkissoon, Ishara

    2001-01-01

    This article traces the development of speech audiometry in the United States and reports on the current status, focusing on the needs of a multilingual population in terms of measuring speech recognition threshold (SRT). It also discusses sociolinguistic considerations, alternative SRT stimuli for second language learners, and research on using…

  17. Word Recognition: Theoretical Issues and Instructional Hints.

    ERIC Educational Resources Information Center

    Smith, Edward E.; Kleiman, Glenn M.

    Research on adult readers' word recognition skills is used in this paper to develop a general information processing model of reading. Stages of the model include feature extraction, interpretation, lexical access, working memory, and integration. Of those stages, particular attention is given to the units of interpretation, speech recoding and…

  18. Speech recognition: Acoustic, phonetic and lexical knowledge

    NASA Astrophysics Data System (ADS)

    Zue, V. W.

    1985-08-01

    During this reporting period we continued to make progress on the acquisition of acoustic-phonetic and lexical knowledge. We completed development of a continuous digit recognition system. The system was constructed to investigate the use of acoustic-phonetic knowledge in a speech recognition system. The significant achievements of this study include the development of a soft-failure procedure for lexical access and the discovery of a set of acoustic-phonetic features for verification. We completed a study of the constraints that lexical stress imposes on word recognition. We found that lexical stress information alone can, on the average, reduce the number of word candidates from a large dictionary by more than 80 percent. In conjunction with this study, we successfully developed a system that automatically determines the stress pattern of a word from the acoustic signal. We performed an acoustic study on the characteristics of nasal consonants and nasalized vowels. We have also developed recognition algorithms for nasal murmurs and nasalized vowels in continuous speech. We finished the preliminary development of a system that aligns a speech waveform with the corresponding phonetic transcription.

  19. Gender Recognition from Point-Light Walkers

    ERIC Educational Resources Information Center

    Pollick, Frank E.; Kay, Jim W.; Heim, Katrin; Stringer, Rebecca

    2005-01-01

    Point-light displays of human gait provide information sufficient to recognize the gender of a walker and are taken as evidence of the exquisite tuning of the visual system to biological motion. The authors revisit this topic with the goals of quantifying human efficiency at gender recognition. To achieve this, the authors first derive an ideal…

  20. Recognition and Assessment of Teaching Quality.

    ERIC Educational Resources Information Center

    Fairbrother, Patricia

    1996-01-01

    Identifies models for consideration of teacher quality and competence in nursing education. Presents a range of evaluation criteria in these categories: preparation, delivery, innovation, communication, self-assessment, instructional management, peer recognition, professional memberships and service, publications, and grants and contracts secured.…

  1. Pattern Recognition by Retina-Like Devices.

    ERIC Educational Resources Information Center

    Weiman, Carl F. R.; Rothstein, Jerome

    This study has investigated some pattern recognition capabilities of devices consisting of arrays of cooperating elements acting in parallel. The problem of recognizing straight lines in general position on the quadratic lattice has been completely solved by applying parallel acting algorithms to a special code for lines on the lattice. The…

  2. Illumination-invariant hand gesture recognition

    NASA Astrophysics Data System (ADS)

    Mendoza-Morales, América I.; Miramontes-Jaramillo, Daniel; Kober, Vitaly

    2015-09-01

    In recent years, human-computer interaction (HCI) has received a lot of interest in industry and science because it provides new ways to interact with modern devices through voice, body, and facial/hand gestures. The application range of the HCI is from easy control of home appliances to entertainment. Hand gesture recognition is a particularly interesting problem because the shape and movement of hands usually are complex and flexible to be able to codify many different signs. In this work we propose a three step algorithm: first, detection of hands in the current frame is carried out; second, hand tracking across the video sequence is performed; finally, robust recognition of gestures across subsequent frames is made. Recognition rate highly depends on non-uniform illumination of the scene and occlusion of hands. In order to overcome these issues we use two Microsoft Kinect devices utilizing combined information from RGB and infrared sensors. The algorithm performance is tested in terms of recognition rate and processing time.

  3. Super-resolution benefit for face recognition

    NASA Astrophysics Data System (ADS)

    Hu, Shuowen; Maschal, Robert; Young, S. Susan; Hong, Tsai Hong; Phillips, Jonathon P.

    2011-06-01

    Vast amounts of video footage are being continuously acquired by surveillance systems on private premises, commercial properties, government compounds, and military installations. Facial recognition systems have the potential to identify suspicious individuals on law enforcement watchlists, but accuracy is severely hampered by the low resolution of typical surveillance footage and the far distance of suspects from the cameras. To improve accuracy, super-resolution can enhance suspect details by utilizing a sequence of low resolution frames from the surveillance footage to reconstruct a higher resolution image for input into the facial recognition system. This work measures the improvement of face recognition with super-resolution in a realistic surveillance scenario. Low resolution and super-resolved query sets are generated using a video database at different eye-to-eye distances corresponding to different distances of subjects from the camera. Performance of a face recognition algorithm using the super-resolved and baseline query sets was calculated by matching against galleries consisting of frontal mug shots. The results show that super-resolution improves performance significantly at the examined mid and close ranges.

  4. Unpacking Recognition and Esteem in School Pedagogies

    ERIC Educational Resources Information Center

    Wulf, Christoph; Bittner, Martin; Clemens, Iris; Kellermann, Ingrid

    2012-01-01

    The article focuses on pedagogical practices of recognition and esteem (Wertschatzung) and on the question of how those practices can be appropriately studied and epistemologically grasped. The investigation involves an inner-city elementary school in a socio-economically problematic district. With regard to the communication forms in this…

  5. Object recognition with hierarchical discriminant saliency networks.

    PubMed

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  6. Object recognition with hierarchical discriminant saliency networks

    PubMed Central

    Han, Sunhyoung; Vasconcelos, Nuno

    2014-01-01

    The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and

  7. Laptop Computer - Based Facial Recognition System Assessment

    SciTech Connect

    R. A. Cain; G. B. Singleton

    2001-03-01

    The objective of this project was to assess the performance of the leading commercial-off-the-shelf (COTS) facial recognition software package when used as a laptop application. We performed the assessment to determine the system's usefulness for enrolling facial images in a database from remote locations and conducting real-time searches against a database of previously enrolled images. The assessment involved creating a database of 40 images and conducting 2 series of tests to determine the product's ability to recognize and match subject faces under varying conditions. This report describes the test results and includes a description of the factors affecting the results. After an extensive market survey, we selected Visionics' FaceIt{reg_sign} software package for evaluation and a review of the Facial Recognition Vendor Test 2000 (FRVT 2000). This test was co-sponsored by the US Department of Defense (DOD) Counterdrug Technology Development Program Office, the National Institute of Justice, and the Defense Advanced Research Projects Agency (DARPA). Administered in May-June 2000, the FRVT 2000 assessed the capabilities of facial recognition systems that were currently available for purchase on the US market. Our selection of this Visionics product does not indicate that it is the ''best'' facial recognition software package for all uses. It was the most appropriate package based on the specific applications and requirements for this specific application. In this assessment, the system configuration was evaluated for effectiveness in identifying individuals by searching for facial images captured from video displays against those stored in a facial image database. An additional criterion was that the system be capable of operating discretely. For this application, an operational facial recognition system would consist of one central computer hosting the master image database with multiple standalone systems configured with duplicates of the master operating in

  8. Integration trumps selection in object recognition.

    PubMed

    Saarela, Toni P; Landy, Michael S

    2015-03-30

    Finding and recognizing objects is a fundamental task of vision. Objects can be defined by several "cues" (color, luminance, texture, etc.), and humans can integrate sensory cues to improve detection and recognition [1-3]. Cortical mechanisms fuse information from multiple cues [4], and shape-selective neural mechanisms can display cue invariance by responding to a given shape independent of the visual cue defining it [5-8]. Selective attention, in contrast, improves recognition by isolating a subset of the visual information [9]. Humans can select single features (red or vertical) within a perceptual dimension (color or orientation), giving faster and more accurate responses to items having the attended feature [10, 11]. Attention elevates neural responses and sharpens neural tuning to the attended feature, as shown by studies in psychophysics and modeling [11, 12], imaging [13-16], and single-cell and neural population recordings [17, 18]. Besides single features, attention can select whole objects [19-21]. Objects are among the suggested "units" of attention because attention to a single feature of an object causes the selection of all of its features [19-21]. Here, we pit integration against attentional selection in object recognition. We find, first, that humans can integrate information near optimally from several perceptual dimensions (color, texture, luminance) to improve recognition. They cannot, however, isolate a single dimension even when the other dimensions provide task-irrelevant, potentially conflicting information. For object recognition, it appears that there is mandatory integration of information from multiple dimensions of visual experience. The advantage afforded by this integration, however, comes at the expense of attentional selection. PMID:25802154

  9. A neuromorphic system for video object recognition

    PubMed Central

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  10. Robust kernel collaborative representation for face recognition

    NASA Astrophysics Data System (ADS)

    Huang, Wei; Wang, Xiaohui; Ma, Yanbo; Jiang, Yuzheng; Zhu, Yinghui; Jin, Zhong

    2015-05-01

    One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

  11. Spoken word recognition without a TRACE.

    PubMed

    Hannagan, Thomas; Magnuson, James S; Grainger, Jonathan

    2013-01-01

    How do we map the rapid input of spoken language onto phonological and lexical representations over time? Attempts at psychologically-tractable computational models of spoken word recognition tend either to ignore time or to transform the temporal input into a spatial representation. TRACE, a connectionist model with broad and deep coverage of speech perception and spoken word recognition phenomena, takes the latter approach, using exclusively time-specific units at every level of representation. TRACE reduplicates featural, phonemic, and lexical inputs at every time step in a large memory trace, with rich interconnections (excitatory forward and backward connections between levels and inhibitory links within levels). As the length of the memory trace is increased, or as the phoneme and lexical inventory of the model is increased to a realistic size, this reduplication of time- (temporal position) specific units leads to a dramatic proliferation of units and connections, begging the question of whether a more efficient approach is possible. Our starting point is the observation that models of visual object recognition-including visual word recognition-have grappled with the problem of spatial invariance, and arrived at solutions other than a fully-reduplicative strategy like that of TRACE. This inspires a new model of spoken word recognition that combines time-specific phoneme representations similar to those in TRACE with higher-level representations based on string kernels: temporally independent (time invariant) diphone and lexical units. This reduces the number of necessary units and connections by several orders of magnitude relative to TRACE. Critically, we compare the new model to TRACE on a set of key phenomena, demonstrating that the new model inherits much of the behavior of TRACE and that the drastic computational savings do not come at the cost of explanatory power. PMID:24058349

  12. A neuromorphic system for video object recognition.

    PubMed

    Khosla, Deepak; Chen, Yang; Kim, Kyungnam

    2014-01-01

    Automated video object recognition is a topic of emerging importance in both defense and civilian applications. This work describes an accurate and low-power neuromorphic architecture and system for real-time automated video object recognition. Our system, Neuormorphic Visual Understanding of Scenes (NEOVUS), is inspired by computational neuroscience models of feed-forward object detection and classification pipelines for processing visual data. The NEOVUS architecture is inspired by the ventral (what) and dorsal (where) streams of the mammalian visual pathway and integrates retinal processing, object detection based on form and motion modeling, and object classification based on convolutional neural networks. The object recognition performance and energy use of the NEOVUS was evaluated by the Defense Advanced Research Projects Agency (DARPA) under the Neovision2 program using three urban area video datasets collected from a mix of stationary and moving platforms. These datasets are challenging and include a large number of objects of different types in cluttered scenes, with varying illumination and occlusion conditions. In a systematic evaluation of five different teams by DARPA on these datasets, the NEOVUS demonstrated the best performance with high object recognition accuracy and the lowest energy consumption. Its energy use was three orders of magnitude lower than two independent state of the art baseline computer vision systems. The dynamic power requirement for the complete system mapped to commercial off-the-shelf (COTS) hardware that includes a 5.6 Megapixel color camera processed by object detection and classification algorithms at 30 frames per second was measured at 21.7 Watts (W), for an effective energy consumption of 5.45 nanoJoules (nJ) per bit of incoming video. These unprecedented results show that the NEOVUS has the potential to revolutionize automated video object recognition toward enabling practical low-power and mobile video processing

  13. Recognition Memory in Reflective and Impulsive Preschool Children

    ERIC Educational Resources Information Center

    Siegel, Alexander W.; And Others

    1973-01-01

    Eight reflective and eight impulsive preschool children were tested in a forced-choice recognition memory task. Reflective children made more correct recognition choices than did impulsive children under all experimental conditions. (ST)

  14. Context Effects In Recognition Memory: Item Order and Unitization

    ERIC Educational Resources Information Center

    Light, Leah L.; Schurr, Sara C.

    1973-01-01

    Study is concerned with the nature of context effects in recognition memory of words. It also examines the relationship between encoding techniques utilized during input and the effects of contextual variation upon subsequent recognition performance. (Author)

  15. Supporting Recognition of Clinical Nurses With the DAISY Award.

    PubMed

    Barnes, Bonnie; Barnes, Mark; Sweeney, Cynthia D

    2016-04-01

    What is meaningful recognition? As a nurse leader, are you prepared to answer that question? Understanding the implications and impact of recognition for nursing staff is a powerful tool for nursing leaders. The DAISY Award is used in more than 2,100 organizations around the globe to give meaning to recognition. Here is a glimpse of the power that recognition can bring to an organization, to its leaders, and most importantly to staff. PMID:27011149

  16. Recognition memory in developmental prosopagnosia: electrophysiological evidence for abnormal routes to face recognition

    PubMed Central

    Burns, Edwin J.; Tree, Jeremy J.; Weidemann, Christoph T.

    2014-01-01

    Dual process models of recognition memory propose two distinct routes for recognizing a face: recollection and familiarity. Recollection is characterized by the remembering of some contextual detail from a previous encounter with a face whereas familiarity is the feeling of finding a face familiar without any contextual details. The Remember/Know (R/K) paradigm is thought to index the relative contributions of recollection and familiarity to recognition performance. Despite researchers measuring face recognition deficits in developmental prosopagnosia (DP) through a variety of methods, none have considered the distinct contributions of recollection and familiarity to recognition performance. The present study examined recognition memory for faces in eight individuals with DP and a group of controls using an R/K paradigm while recording electroencephalogram (EEG) data at the scalp. Those with DP were found to produce fewer correct “remember” responses and more false alarms than controls. EEG results showed that posterior “remember” old/new effects were delayed and restricted to the right posterior (RP) area in those with DP in comparison to the controls. A posterior “know” old/new effect commonly associated with familiarity for faces was only present in the controls whereas individuals with DP exhibited a frontal “know” old/new effect commonly associated with words, objects and pictures. These results suggest that individuals with DP do not utilize normal face-specific routes when making face recognition judgments but instead process faces using a pathway more commonly associated with objects. PMID:25177283

  17. Complexity reduction with recognition rate maintained for online handwritten Japanese text recognition

    NASA Astrophysics Data System (ADS)

    Gao, Jinfeng; Zhu, Bilan; Nakagawa, Masaki

    2012-01-01

    The paper presents complexity reduction of an on-line handwritten Japanese text recognition system by selecting an optimal off-line recognizer in combination with an on-line recognizer, geometric context evaluation and linguistic context evaluation. The result is that a surprisingly small off-line recognizer, which alone is weak, produces nearly the best recognition rate in combination with other evaluation factors in remarkably small space and time complexity. Generally speaking, lower dimensions with less principle components produce a smaller set of prototypes, which reduce memory-cost and time-cost. It degrades the recognition rate, however, so that we need to compromise them. In an evaluation function with the above-mentioned multiple factors combined, the configuration of only 50 dimensions with as little as 5 principle components for the off-line recognizer keeps almost the best accuracy 97.87% (the best accuracy 97.92%) for text recognition while it suppresses the total memory-cost from 99.4 MB down to 32 MB and the average time-cost of character recognition for text recognition from 0.1621 ms to 0.1191 ms compared with the traditional offline recognizer with 160 dimensions and 50 principle components.

  18. Interactive object recognition assistance: an approach to recognition starting from target objects

    NASA Astrophysics Data System (ADS)

    Geisler, Juergen; Littfass, Michael

    1999-07-01

    Recognition of target objects in remotely sensed imagery required detailed knowledge about the target object domain as well as about mapping properties of the sensing system. The art of object recognition is to combine both worlds appropriately and to provide models of target appearance with respect to sensor characteristics. Common approaches to support interactive object recognition are either driven from the sensor point of view and address the problem of displaying images in a manner adequate to the sensing system. Or they focus on target objects and provide exhaustive encyclopedic information about this domain. Our paper discusses an approach to assist interactive object recognition based on knowledge about target objects and taking into account the significance of object features with respect to characteristics of the sensed imagery, e.g. spatial and spectral resolution. An `interactive recognition assistant' takes the image analyst through the interpretation process by indicating step-by-step the respectively most significant features of objects in an actual set of candidates. The significance of object features is expressed by pregenerated trees of significance, and by the dynamic computation of decision relevance for every feature at each step of the recognition process. In the context of this approach we discuss the question of modeling and storing the multisensorial/multispectral appearances of target objects and object classes as well as the problem of an adequate dynamic human-machine-interface that takes into account various mental models of human image interpretation.

  19. Automatic TLI recognition system, user`s guide

    SciTech Connect

    Lassahn, G.D.

    1997-02-01

    This report describes how to use an automatic target recognition system (version 14). In separate volumes are a general description of the ATR system, Automatic TLI Recognition System, General Description, and a programmer`s manual, Automatic TLI Recognition System, Programmer`s Guide.

  20. 46 CFR 8.240 - Application for recognition.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... ALTERNATIVES Recognition of a Classification Society § 8.240 Application for recognition. (a) A classification society must apply for recognition in writing to the Commandant (CG-521). (b) An application must indicate which specific authority the classification society seeks to have delegated. (c) Upon verification...

  1. 46 CFR 8.260 - Revocation of classification society recognition.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Revocation of classification society recognition. 8.260... VESSEL INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.260 Revocation of classification society recognition. A recognized classification society which fails to maintain the...

  2. 46 CFR 8.220 - Recognition of a classification society.

    Code of Federal Regulations, 2010 CFR

    2010-10-01

    ... 46 Shipping 1 2010-10-01 2010-10-01 false Recognition of a classification society. 8.220 Section 8... INSPECTION ALTERNATIVES Recognition of a Classification Society § 8.220 Recognition of a classification society. (a) A classification society must be recognized by the Commandant before it may receive...

  3. Recognition and Accountability: Sole Parent Postgraduates in University Conditions

    ERIC Educational Resources Information Center

    Hook, Genine A.

    2015-01-01

    This paper aims to examine some of ways sole parents sought recognition as postgraduate students in Australian universities. Judith Butler's theory of recognition notes that recognition is always partial and any account we give of ourselves must be given to another. Participants articulated that supervisors were critical in the process of…

  4. 75 FR 70696 - QPS Evaluation Services Inc.; Application for Recognition

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-11-18

    ... Occupational Safety and Health Administration QPS Evaluation Services Inc.; Application for Recognition AGENCY... application of QPS Evaluation Services Inc. for recognition as a Nationally Recognized Testing Laboratory, and...) is providing notice that QPS Evaluation Services Inc. (QPS) applied for recognition as a...

  5. The recognition heuristic: a review of theory and tests.

    PubMed

    Pachur, Thorsten; Todd, Peter M; Gigerenzer, Gerd; Schooler, Lael J; Goldstein, Daniel G

    2011-01-01

    The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect - the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

  6. 34 CFR 602.30 - Activities covered by recognition procedures.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 34 Education 3 2013-07-01 2013-07-01 false Activities covered by recognition procedures. 602.30... POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION THE SECRETARY'S RECOGNITION OF ACCREDITING AGENCIES The Recognition Process Application and Review by Department Staff § 602.30 Activities covered by...

  7. 34 CFR 602.30 - Activities covered by recognition procedures.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 34 Education 3 2011-07-01 2011-07-01 false Activities covered by recognition procedures. 602.30... POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION THE SECRETARY'S RECOGNITION OF ACCREDITING AGENCIES The Recognition Process Application and Review by Department Staff § 602.30 Activities covered by...

  8. 37 CFR 2.17 - Recognition for representation.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2010-07-01 2010-07-01 false Recognition for... Persons § 2.17 Recognition for representation. (a) Authority to practice in trademark cases. Only an... party to a proceeding before the Office in a trademark case. (b)(1) Recognition of practitioner...

  9. 38 CFR 14.628 - Recognition of organizations.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 38 Pensions, Bonuses, and Veterans' Relief 1 2012-07-01 2012-07-01 false Recognition of... Affairs Claimants; Recognition of Organizations, Accredited Representatives, Attorneys, Agents; Rules of Practice and Information Concerning Fees, 38 U.s.c. 5901-5905 § 14.628 Recognition of...

  10. 34 CFR 602.30 - Activities covered by recognition procedures.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 34 Education 3 2012-07-01 2012-07-01 false Activities covered by recognition procedures. 602.30... POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION THE SECRETARY'S RECOGNITION OF ACCREDITING AGENCIES The Recognition Process Application and Review by Department Staff § 602.30 Activities covered by...

  11. 37 CFR 2.17 - Recognition for representation.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2012-07-01 2012-07-01 false Recognition for... Persons § 2.17 Recognition for representation. (a) Authority to practice in trademark cases. Only an... party to a proceeding before the Office in a trademark case. (b)(1) Recognition of practitioner...

  12. 34 CFR 602.30 - Activities covered by recognition procedures.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 34 Education 3 2014-07-01 2014-07-01 false Activities covered by recognition procedures. 602.30... POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION THE SECRETARY'S RECOGNITION OF ACCREDITING AGENCIES The Recognition Process Application and Review by Department Staff § 602.30 Activities covered by...

  13. 34 CFR 602.30 - Activities covered by recognition procedures.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 34 Education 3 2010-07-01 2010-07-01 false Activities covered by recognition procedures. 602.30... POSTSECONDARY EDUCATION, DEPARTMENT OF EDUCATION THE SECRETARY'S RECOGNITION OF ACCREDITING AGENCIES The Recognition Process Application and Review by Department Staff § 602.30 Activities covered by...

  14. 37 CFR 2.17 - Recognition for representation.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2014-07-01 2014-07-01 false Recognition for... Persons § 2.17 Recognition for representation. (a) Authority to practice in trademark cases. Only an... party to a proceeding before the Office in a trademark case. (b)(1) Recognition of practitioner...

  15. 37 CFR 2.17 - Recognition for representation.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2013-07-01 2013-07-01 false Recognition for... Persons § 2.17 Recognition for representation. (a) Authority to practice in trademark cases. Only an... party to a proceeding before the Office in a trademark case. (b)(1) Recognition of practitioner...

  16. 37 CFR 2.17 - Recognition for representation.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 37 Patents, Trademarks, and Copyrights 1 2011-07-01 2011-07-01 false Recognition for... Persons § 2.17 Recognition for representation. (a) Authority to practice in trademark cases. Only an... party to a proceeding before the Office in a trademark case. (b)(1) Recognition of practitioner...

  17. Developing Recognition Programs for Units within Student Affairs.

    ERIC Educational Resources Information Center

    Avery, Cynthia M.

    2001-01-01

    According to many psychologists, the connections between motivation and rewards and recognition are crucial to employee satisfaction. A plan for developing a multi-layered recognition program within a division of student affairs is described. These recognitions programs are designed taking into account the differences in perceptions of awards by…

  18. Accurate forced-choice recognition without awareness of memory retrieval.

    PubMed

    Voss, Joel L; Baym, Carol L; Paller, Ken A

    2008-06-01

    Recognition confidence and the explicit awareness of memory retrieval commonly accompany accurate responding in recognition tests. Memory performance in recognition tests is widely assumed to measure explicit memory, but the generality of this assumption is questionable. Indeed, whether recognition in nonhumans is always supported by explicit memory is highly controversial. Here we identified circumstances wherein highly accurate recognition was unaccompanied by hallmark features of explicit memory. When memory for kaleidoscopes was tested using a two-alternative forced-choice recognition test with similar foils, recognition was enhanced by an attentional manipulation at encoding known to degrade explicit memory. Moreover, explicit recognition was most accurate when the awareness of retrieval was absent. These dissociations between accuracy and phenomenological features of explicit memory are consistent with the notion that correct responding resulted from experience-dependent enhancements of perceptual fluency with specific stimuli--the putative mechanism for perceptual priming effects in implicit memory tests. This mechanism may contribute to recognition performance in a variety of frequently-employed testing circumstances. Our results thus argue for a novel view of recognition, in that analyses of its neurocognitive foundations must take into account the potential for both (1) recognition mechanisms allied with implicit memory and (2) recognition mechanisms allied with explicit memory. PMID:18519546

  19. How Similar are Context Effects in Recognition and Recall?

    ERIC Educational Resources Information Center

    Hunt, R. Reed

    1975-01-01

    The context effect in recognition memory has been attributed to retrieval failure following a context change. Since this inference is based in part upon the similarity of context effects in recognition and recall, two experiments were conducted to examine further the similarity of context effects upon recognition and recall. (Editor)

  20. The Recognition Heuristic: A Review of Theory and Tests

    PubMed Central

    Pachur, Thorsten; Todd, Peter M.; Gigerenzer, Gerd; Schooler, Lael J.; Goldstein, Daniel G.

    2011-01-01

    The recognition heuristic is a prime example of how, by exploiting a match between mind and environment, a simple mental strategy can lead to efficient decision making. The proposal of the heuristic initiated a debate about the processes underlying the use of recognition in decision making. We review research addressing four key aspects of the recognition heuristic: (a) that recognition is often an ecologically valid cue; (b) that people often follow recognition when making inferences; (c) that recognition supersedes further cue knowledge; (d) that its use can produce the less-is-more effect – the phenomenon that lesser states of recognition knowledge can lead to more accurate inferences than more complete states. After we contrast the recognition heuristic to other related concepts, including availability and fluency, we carve out, from the existing findings, some boundary conditions of the use of the recognition heuristic as well as key questions for future research. Moreover, we summarize developments concerning the connection of the recognition heuristic with memory models. We suggest that the recognition heuristic is used adaptively and that, compared to other cues, recognition seems to have a special status in decision making. Finally, we discuss how systematic ignorance is exploited in other cognitive mechanisms (e.g., estimation and preference). PMID:21779266

  1. Peer-to-Peer Recognition of Learning in Open Education

    ERIC Educational Resources Information Center

    Schmidt, Jan Philipp; Geith, Christine; Haklev, Stian; Thierstein, Joel

    2009-01-01

    Recognition in education is the acknowledgment of learning achievements. Accreditation is certification of such recognition by an institution, an organization, a government, a community, etc. There are a number of assessment methods by which learning can be evaluated (exam, practicum, etc.) for the purpose of recognition and accreditation, and…

  2. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2011 CFR

    2011-07-01

    ... 31 Money and Finance:Treasury 2 2011-07-01 2011-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  3. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2013 CFR

    2013-07-01

    ... 31 Money and Finance:Treasury 2 2013-07-01 2013-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  4. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2010 CFR

    2010-07-01

    ... 31 Money and Finance: Treasury 2 2010-07-01 2010-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  5. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2014 CFR

    2014-07-01

    ... 31 Money and Finance: Treasury 2 2014-07-01 2014-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  6. 31 CFR 223.12 - Recognition as reinsurer.

    Code of Federal Regulations, 2012 CFR

    2012-07-01

    ... 31 Money and Finance:Treasury 2 2012-07-01 2012-07-01 false Recognition as reinsurer. 223.12... UNITED STATES § 223.12 Recognition as reinsurer. (a) Application by U.S. company. Any company organized under the laws of the United States or of any State thereof, wishing to apply for recognition as...

  7. Relations among Early Object Recognition Skills: Objects and Letters

    ERIC Educational Resources Information Center

    Augustine, Elaine; Jones, Susan S.; Smith, Linda B.; Longfield, Erica

    2015-01-01

    Human visual object recognition is multifaceted and comprised of several domains of expertise. Developmental relations between young children's letter recognition and their 3-dimensional object recognition abilities are implicated on several grounds but have received little research attention. Here, we ask how preschoolers' success in recognizing…

  8. Improved Open-Microphone Speech Recognition

    NASA Technical Reports Server (NTRS)

    Abrash, Victor

    2002-01-01

    Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken

  9. Improved Open-Microphone Speech Recognition

    NASA Astrophysics Data System (ADS)

    Abrash, Victor

    2002-12-01

    Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken

  10. Transfer-Appropriate Processing in Recognition Memory: Perceptual and Conceptual Effects on Recognition Memory Depend on Task Demands

    ERIC Educational Resources Information Center

    Parks, Colleen M.

    2013-01-01

    Research examining the importance of surface-level information to familiarity in recognition memory tasks is mixed: Sometimes it affects recognition and sometimes it does not. One potential explanation of the inconsistent findings comes from the ideas of dual process theory of recognition and the transfer-appropriate processing framework, which…

  11. Combined Hand Gesture — Speech Model for Human Action Recognition

    PubMed Central

    Cheng, Sheng-Tzong; Hsu, Chih-Wei; Li, Jian-Pan

    2013-01-01

    This study proposes a dynamic hand gesture detection technology to effectively detect dynamic hand gesture areas, and a hand gesture recognition technology to improve the dynamic hand gesture recognition rate. Meanwhile, the corresponding relationship between state sequences in hand gesture and speech models is considered by integrating speech recognition technology with a multimodal model, thus improving the accuracy of human behavior recognition. The experimental results proved that the proposed method can effectively improve human behavior recognition accuracy and the feasibility of system applications. Experimental results verified that the multimodal gesture-speech model provided superior accuracy when compared to the single modal versions. PMID:24351628

  12. Towards behaviour-recognition-based video surveillance

    NASA Astrophysics Data System (ADS)

    Gong, Shaogang

    2004-12-01

    We present the latest results on learnable stochastic temporal models for automatic event and behaviour recognition in CCTV surveillance video. We introduce a novel approach to modelling and recognising complex activities involving simultaneous movement of multiple objects. Our approach differs from most previous work in that the visual understanding of activity is based on visual event detection and reasoning instead of object tracking and trajectory matching. Dynamic probabilistic graph models are exploited for modelling the temporal relationships among a set of different object temporal events. Typical applications of this technology include automatic semantic video content analysis, profiling and indexing of salient event and behaviour captured in CCTV video, and the early recognition of atypical behaviour in scenes where such behaviour could lead to a threat to safety.

  13. An improved Camshift algorithm for target recognition

    NASA Astrophysics Data System (ADS)

    Fu, Min; Cai, Chao; Mao, Yusu

    2015-12-01

    Camshift algorithm and three frame difference algorithm are the popular target recognition and tracking methods. Camshift algorithm requires a manual initialization of the search window, which needs the subjective error and coherence, and only in the initialization calculating a color histogram, so the color probability model cannot be updated continuously. On the other hand, three frame difference method does not require manual initialization search window, it can make full use of the motion information of the target only to determine the range of motion. But it is unable to determine the contours of the object, and can not make use of the color information of the target object. Therefore, the improved Camshift algorithm is proposed to overcome the disadvantages of the original algorithm, the three frame difference operation is combined with the object's motion information and color information to identify the target object. The improved Camshift algorithm is realized and shows better performance in the recognition and tracking of the target.

  14. Average Gait Differential Image Based Human Recognition

    PubMed Central

    Chen, Jinyan; Liu, Jiansheng

    2014-01-01

    The difference between adjacent frames of human walking contains useful information for human gait identification. Based on the previous idea a silhouettes difference based human gait recognition method named as average gait differential image (AGDI) is proposed in this paper. The AGDI is generated by the accumulation of the silhouettes difference between adjacent frames. The advantage of this method lies in that as a feature image it can preserve both the kinetic and static information of walking. Comparing to gait energy image (GEI), AGDI is more fit to representation the variation of silhouettes during walking. Two-dimensional principal component analysis (2DPCA) is used to extract features from the AGDI. Experiments on CASIA dataset show that AGDI has better identification and verification performance than GEI. Comparing to PCA, 2DPCA is a more efficient and less memory storage consumption feature extraction method in gait based recognition. PMID:24895648

  15. Extended Target Recognition in Cognitive Radar Networks

    PubMed Central

    Wei, Yimin; Meng, Huadong; Liu, Yimin; Wang, Xiqin

    2010-01-01

    We address the problem of adaptive waveform design for extended target recognition in cognitive radar networks. A closed-loop active target recognition radar system is extended to the case of a centralized cognitive radar network, in which a generalized likelihood ratio (GLR) based sequential hypothesis testing (SHT) framework is employed. Using Doppler velocities measured by multiple radars, the target aspect angle for each radar is calculated. The joint probability of each target hypothesis is then updated using observations from different radar line of sights (LOS). Based on these probabilities, a minimum correlation algorithm is proposed to adaptively design the transmit waveform for each radar in an amplitude fluctuation situation. Simulation results demonstrate performance improvements due to the cognitive radar network and adaptive waveform design. Our minimum correlation algorithm outperforms the eigen-waveform solution and other non-cognitive waveform design approaches. PMID:22163464

  16. Photoswitchable gel assembly based on molecular recognition.

    PubMed

    Yamaguchi, Hiroyasu; Kobayashi, Yuichiro; Kobayashi, Ryosuke; Takashima, Yoshinori; Hashidzume, Akihito; Harada, Akira

    2012-01-01

    The formation of effective and precise linkages in bottom-up or top-down processes is important for the development of self-assembled materials. Self-assembly through molecular recognition events is a powerful tool for producing functionalized materials. Photoresponsive molecular recognition systems can permit the creation of photoregulated self-assembled macroscopic objects. Here we demonstrate that macroscopic gel assembly can be highly regulated through photoisomerization of an azobenzene moiety that interacts differently with two host molecules. A photoregulated gel assembly system is developed using polyacrylamide-based hydrogels functionalized with azobenzene (guest) or cyclodextrin (host) moieties. Reversible adhesion and dissociation of the host gel from the guest gel may be controlled by photoirradiation. The differential affinities of α-cyclodextrin or β-cyclodextrin for the trans-azobenzene and cis-azobenzene are employed in the construction of a photoswitchable gel assembly system. PMID:22215078

  17. Photoswitchable gel assembly based on molecular recognition

    PubMed Central

    Yamaguchi, Hiroyasu; Kobayashi, Yuichiro; Kobayashi, Ryosuke; Takashima, Yoshinori; Hashidzume, Akihito; Harada, Akira

    2012-01-01

    The formation of effective and precise linkages in bottom-up or top-down processes is important for the development of self-assembled materials. Self-assembly through molecular recognition events is a powerful tool for producing functionalized materials. Photoresponsive molecular recognition systems can permit the creation of photoregulated self-assembled macroscopic objects. Here we demonstrate that macroscopic gel assembly can be highly regulated through photoisomerization of an azobenzene moiety that interacts differently with two host molecules. A photoregulated gel assembly system is developed using polyacrylamide-based hydrogels functionalized with azobenzene (guest) or cyclodextrin (host) moieties. Reversible adhesion and dissociation of the host gel from the guest gel may be controlled by photoirradiation. The differential affinities of α-cyclodextrin or β-cyclodextrin for the trans-azobenzene and cis-azobenzene are employed in the construction of a photoswitchable gel assembly system. PMID:22215078

  18. Pattern recognition and control in manipulation

    NASA Technical Reports Server (NTRS)

    Bejczy, A. K.; Tomovic, R.

    1976-01-01

    A new approach to the use of sensors in manipulator or robot control is discussed. The concept addresses the problem of contact or near-contact type of recognition of three-dimensional forms of objects by proprioceptive and/or exteroceptive sensors integrated with the terminal device. This recognition of object shapes both enhances and simplifies the automation of object handling. Several examples have been worked out for the 'Belgrade hand' and for a parallel jaw terminal device, both equipped with proprioceptive (position) and exteroceptive (proximity) sensors. The control applications are discussed in the framework of a multilevel man-machine system control. The control applications create interesting new issues which, in turn, invite novel theoretical considerations. An important issue is the problem of stability in control when the control is referenced to patterns.

  19. Photonics: From target recognition to lesion detection

    NASA Technical Reports Server (NTRS)

    Henry, E. Michael

    1994-01-01

    Since 1989, Martin Marietta has invested in the development of an innovative concept for robust real-time pattern recognition for any two-dimensioanal sensor. This concept has been tested in simulation, and in laboratory and field hardware, for a number of DOD and commercial uses from automatic target recognition to manufacturing inspection. We have now joined Rose Health Care Systems in developing its use for medical diagnostics. The concept is based on determining regions of interest by using optical Fourier bandpassing as a scene segmentation technique, enhancing those regions using wavelet filters, passing the enhanced regions to a neural network for analysis and initial pattern identification, and following this initial identification with confirmation by optical correlation. The optical scene segmentation and pattern confirmation are performed by the same optical module. The neural network is a recursive error minimization network with a small number of connections and nodes that rapidly converges to a global minimum.

  20. Shape recognition with scale and rotation invariance

    NASA Astrophysics Data System (ADS)

    Schau, Harvey C.

    1992-02-01

    A technique for shape recognition test is invariant to scale and rotation is presented. This technique employs the number of bit quads, the basic 2 X 2 element of binary (0,1) imagery, of each object. The feature vector is a scaled version of the number of bit quads, which allows a distance to be defined between unknown objects and a collection of known prototypes. Recognition is accomplished by utilizing this distance metric as a classifier. An example is provided that recognizes an automobile shape from a set of six prototypes. Several experiments are performed that change the scale and relative rotation of the unknown. In all cases the correct automobile is identified from the set of six prototypes. A second example considers the effects of boundary noise on classification and points out the advantage of employing noise smoothing prior to feature extraction. The technique presented has the advantage of simplicity, pipeline implementation, and low storage requirements.

  1. Feature recognition applications in mesh generation

    SciTech Connect

    Tautges, T.J.; Liu, S.S.; Lu, Y.; Kraftcheck, J.; Gadh, R.

    1997-06-01

    The use of feature recognition as part of an overall decomposition-based hexahedral meshing approach is described in this paper. The meshing approach consists of feature recognition, using a c-loop or hybrid c-loop method, and the use of cutting surfaces to decompose the solid model. These steps are part of an iterative process, which proceeds either until no more features can be recognized or until the model has been completely decomposed into meshable sub-volumes. This method can greatly reduce the time required to generate an all-hexahedral mesh, either through the use of more efficient meshing algorithms on more of the geometry or by reducing the amount of manual decomposition required to mesh a volume.

  2. Supramolecular Polymerization Engineered with Molecular Recognition.

    PubMed

    Haino, Takeharu

    2015-10-01

    Supramolecular polymeric assemblies represent an emerging, promising class of molecular assemblies with enormous versatility compared with their covalent polymeric counterparts. Although a large number of host-guest motifs have been produced over the history of supramolecular chemistry, only a limited number of recognition motifs have been utilized as supramolecular connections in polymeric assemblies. This account describes the molecular recognition of host molecules based on calix[5]arene and bisporphyrin that demonstrate unique guest encapsulations; subsequently, these host-guest motifs are applied to the synthesis of supramolecular polymers that display polymer-like properties in solution and solid states. In addition, new bisresorcinarenes are developed to form supramolecular polymers that are connected via a rim-to-rim hydrogen-bonded dimeric structure, which is composed of two resorcinarene moieties. PMID:26178364

  3. Audio-visual affective expression recognition

    NASA Astrophysics Data System (ADS)

    Huang, Thomas S.; Zeng, Zhihong

    2007-11-01

    Automatic affective expression recognition has attracted more and more attention of researchers from different disciplines, which will significantly contribute to a new paradigm for human computer interaction (affect-sensitive interfaces, socially intelligent environments) and advance the research in the affect-related fields including psychology, psychiatry, and education. Multimodal information integration is a process that enables human to assess affective states robustly and flexibly. In order to understand the richness and subtleness of human emotion behavior, the computer should be able to integrate information from multiple sensors. We introduce in this paper our efforts toward machine understanding of audio-visual affective behavior, based on both deliberate and spontaneous displays. Some promising methods are presented to integrate information from both audio and visual modalities. Our experiments show the advantage of audio-visual fusion in affective expression recognition over audio-only or visual-only approaches.

  4. Attention, biological motion, and action recognition.

    PubMed

    Thompson, James; Parasuraman, Raja

    2012-01-01

    Interacting with others in the environment requires that we perceive and recognize their movements and actions. Neuroimaging and neuropsychological studies have indicated that a number of brain regions, particularly the superior temporal sulcus, are involved in a number of processes essential for action recognition, including the processing of biological motion and processing the intentions of actions. We review the behavioral and neuroimaging evidence suggesting that while some aspects of action recognition might be rapid and effective, they are not necessarily automatic. Attention is particularly important when visual information about actions is degraded or ambiguous, or if competing information is present. We present evidence indicating that neural responses associated with the processing of biological motion are strongly modulated by attention. In addition, behavioral and neuroimaging evidence shows that drawing inferences from the actions of others is attentionally demanding. The role of attention in action observation has implications for everyday social interactions and workplace applications that depend on observing, understanding and interpreting actions. PMID:21640836

  5. Static hand gesture recognition from a video

    NASA Astrophysics Data System (ADS)

    Rokade, Rajeshree S.; Doye, Dharmpal

    2011-10-01

    A sign language (also signed language) is a language which, instead of acoustically conveyed sound patterns, uses visually transmitted sign patterns to convey meaning- "simultaneously combining hand shapes, orientation and movement of the hands". Sign languages commonly develop in deaf communities, which can include interpreters, friends and families of deaf people as well as people who are deaf or hard of hearing themselves. In this paper, we proposed a novel system for recognition of static hand gestures from a video, based on Kohonen neural network. We proposed algorithm to separate out key frames, which include correct gestures from a video sequence. We segment, hand images from complex and non uniform background. Features are extracted by applying Kohonen on key frames and recognition is done.

  6. Protein-targeted corona phase molecular recognition

    PubMed Central

    Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

    2016-01-01

    Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications. PMID:26742890

  7. Protein-targeted corona phase molecular recognition

    NASA Astrophysics Data System (ADS)

    Bisker, Gili; Dong, Juyao; Park, Hoyoung D.; Iverson, Nicole M.; Ahn, Jiyoung; Nelson, Justin T.; Landry, Markita P.; Kruss, Sebastian; Strano, Michael S.

    2016-01-01

    Corona phase molecular recognition (CoPhMoRe) uses a heteropolymer adsorbed onto and templated by a nanoparticle surface to recognize a specific target analyte. This method has not yet been extended to macromolecular analytes, including proteins. Herein we develop a variant of a CoPhMoRe screening procedure of single-walled carbon nanotubes (SWCNT) and use it against a panel of human blood proteins, revealing a specific corona phase that recognizes fibrinogen with high selectivity. In response to fibrinogen binding, SWCNT fluorescence decreases by >80% at saturation. Sequential binding of the three fibrinogen nodules is suggested by selective fluorescence quenching by isolated sub-domains and validated by the quenching kinetics. The fibrinogen recognition also occurs in serum environment, at the clinically relevant fibrinogen concentrations in the human blood. These results open new avenues for synthetic, non-biological antibody analogues that recognize biological macromolecules, and hold great promise for medical and clinical applications.

  8. Gender recognition based on face geometric features

    NASA Astrophysics Data System (ADS)

    Xiao, Jie; Guo, Zhaoli; Cai, Chao

    2013-10-01

    Automatic gender recognition based on face images plays an important role in computer vision and machine vision. In this paper, a novel and simple gender recognition method based on face geometric features is proposed. The method is divided in three steps. Firstly, Pre-processing step provides standard face images for feature extraction. Secondly, Active Shape Model (ASM) is used to extract geometric features in frontal face images. Thirdly, Adaboost classifier is chosen to separate the two classes (male and female). We tested it on 2570 pictures (1420 males and 1150 females) downloaded from the internet, and encouraging results were acquired. The comparison of the proposed geometric feature based method and the full facial image based method demonstrats its superiority.

  9. Epileptic activity recognition in EEG recording

    NASA Astrophysics Data System (ADS)

    Diambra, L.; de Figueiredo, J. C. Bastos; Malta, C. P.

    1999-12-01

    We apply Approximate Entropy (ApEn) algorithm in order to recognize epileptic activity in electroencephalogram recordings. ApEn is a recently developed statistical quantity for quantifying regularity and complexity. Our approach is illustrated regarding different types of epileptic activity. In all segments associated with epileptic activity analyzed here the complexity of the signal measured by ApEn drops abruptly. This fact can be useful for automatic recognition and detection of epileptic seizures.

  10. New FASB standard addresses revenue recognition considerations.

    PubMed

    McKee, Thomas E

    2015-12-01

    Healthcare organizations are expected to apply the following steps in revenue recognition under the new standard issued in May 2014 by the Financial Accounting Standards Board: Identify the customer contract. Identify the performance obligations in the contract. Determine the transaction price. Allocate the transaction price to the performance obligations in the contract. Recognize revenue when--or in some circumstances, as--the entity satisfies the performance obligation. PMID:26793947

  11. Biochip microsystem for bioinformatics recognition and analysis

    NASA Technical Reports Server (NTRS)

    Lue, Jaw-Chyng (Inventor); Fang, Wai-Chi (Inventor)

    2011-01-01

    A system with applications in pattern recognition, or classification, of DNA assay samples. Because DNA reference and sample material in wells of an assay may be caused to fluoresce depending upon dye added to the material, the resulting light may be imaged onto an embodiment comprising an array of photodetectors and an adaptive neural network, with applications to DNA analysis. Other embodiments are described and claimed.

  12. A multifunction recognition operator for telerobotic vision

    NASA Technical Reports Server (NTRS)

    Goode, P. W., IV

    1986-01-01

    Research on developing an operator capable of performing the various subtasks required of a telerobot's vision sensor is reported. The operator uses a goal-driven matching technique which is an application of a linear programming method that readily adapts to the elastic template matching approach to pattern recognition. Four applications of the operator are discussed: (1) three-space location of an isolated object; (2) shape determination of isolated planar figures; (3) image compression/restoration; and (4) shape decomposition.

  13. Invariant object recognition based on extended fragments.

    PubMed

    Bart, Evgeniy; Hegdé, Jay

    2012-01-01

    Visual appearance of natural objects is profoundly affected by viewing conditions such as viewpoint and illumination. Human subjects can nevertheless compensate well for variations in these viewing conditions. The strategies that the visual system uses to accomplish this are largely unclear. Previous computational studies have suggested that in principle, certain types of object fragments (rather than whole objects) can be used for invariant recognition. However, whether the human visual system is actually capable of using this strategy remains unknown. Here, we show that human observers can achieve illumination invariance by using object fragments that carry the relevant information. To determine this, we have used novel, but naturalistic, 3-D visual objects called "digital embryos." Using novel instances of whole embryos, not fragments, we trained subjects to recognize individual embryos across illuminations. We then tested the illumination-invariant object recognition performance of subjects using fragments. We found that the performance was strongly correlated with the mutual information (MI) of the fragments, provided that MI value took variations in illumination into consideration. This correlation was not attributable to any systematic differences in task difficulty between different fragments. These results reveal two important principles of invariant object recognition. First, the subjects can achieve invariance at least in part by compensating for the changes in the appearance of small local features, rather than of whole objects. Second, the subjects do not always rely on generic or pre-existing invariance of features (i.e., features whose appearance remains largely unchanged by variations in illumination), and are capable of using learning to compensate for appearance changes when necessary. These psychophysical results closely fit the predictions of earlier computational studies of fragment-based invariant object recognition. PMID:22936910

  14. Event identification by acoustic signature recognition

    SciTech Connect

    Dress, W.B.; Kercel, S.W.

    1995-07-01

    Many events of interest to the security commnnity produce acoustic emissions that are, in principle, identifiable as to cause. Some obvious examples are gunshots, breaking glass, takeoffs and landings of small aircraft, vehicular engine noises, footsteps (high frequencies when on gravel, very low frequencies. when on soil), and voices (whispers to shouts). We are investigating wavelet-based methods to extract unique features of such events for classification and identification. We also discuss methods of classification and pattern recognition specifically tailored for acoustic signatures obtained by wavelet analysis. The paper is divided into three parts: completed work, work in progress, and future applications. The completed phase has led to the successful recognition of aircraft types on landing and takeoff. Both small aircraft (twin-engine turboprop) and large (commercial airliners) were included in the study. The project considered the design of a small, field-deployable, inexpensive device. The techniques developed during the aircraft identification phase were then adapted to a multispectral electromagnetic interference monitoring device now deployed in a nuclear power plant. This is a general-purpose wavelet analysis engine, spanning 14 octaves, and can be adapted for other specific tasks. Work in progress is focused on applying the methods previously developed to speaker identification. Some of the problems to be overcome include recognition of sounds as voice patterns and as distinct from possible background noises (e.g., music), as well as identification of the speaker from a short-duration voice sample. A generalization of the completed work and the work in progress is a device capable of classifying any number of acoustic events-particularly quasi-stationary events such as engine noises and voices and singular events such as gunshots and breaking glass. We will show examples of both kinds of events and discuss their recognition likelihood.

  15. Lipopolysaccharide recognition, CD14, and lipopolysaccharide receptors.

    PubMed

    Ingalls, R R; Heine, H; Lien, E; Yoshimura, A; Golenbock, D

    1999-06-01

    The ability of a host to sense invasion by a pathogenic organism, and to respond appropriately to control infection, is paramount to survival. To that end, an array of receptors and binding proteins has evolved as part of the innate immune system to detect Gram-negative bacteria. This article reviews the role of CD14, other LPS binding proteins, and the Toll family of receptors in the innate recognition of bacterial lipopolysaccharide. PMID:10340170

  16. Hybrid pyramid/neural network object recognition

    NASA Astrophysics Data System (ADS)

    Anandan, P.; Burt, Peter J.; Pearson, John C.; Spence, Clay D.

    1994-02-01

    This work concerns computationally efficient computer vision methods for the search for and identification of small objects in large images. The approach combines neural network pattern recognition with pyramid-based coarse-to-fine search, in a way that eliminates the drawbacks of each method when used by itself and, in addition, improves object identification through learning and exploiting the low-resolution image context associated with the objects. The presentation will describe the system architecture and the performance on illustrative problems.

  17. A Fuzzy Aproach For Facial Emotion Recognition

    NASA Astrophysics Data System (ADS)

    Gîlcă, Gheorghe; Bîzdoacă, Nicu-George

    2015-09-01

    This article deals with an emotion recognition system based on the fuzzy sets. Human faces are detected in images with the Viola - Jones algorithm and for its tracking in video sequences we used the Camshift algorithm. The detected human faces are transferred to the decisional fuzzy system, which is based on the variable fuzzyfication measurements of the face: eyebrow, eyelid and mouth. The system can easily determine the emotional state of a person.

  18. Gait recognition based on Kinect sensor

    NASA Astrophysics Data System (ADS)

    Ahmed, Mohammed; Al-Jawad, Naseer; Sabir, Azhin T.

    2014-05-01

    This paper presents gait recognition based on human skeleton and trajectory of joint points captured by Microsoft Kinect sensor. In this paper Two sets of dynamic features are extracted during one gait cycle: the first is Horizontal Distance Features (HDF) that is based on the distances between (Ankles, knees, hands, shoulders), the second set is the Vertical Distance Features (VDF) that provide significant information of human gait extracted from the height to the ground of (hand, shoulder, and ankles) during one gait cycle. Extracting these two sets of feature are difficult and not accurate based on using traditional camera, therefore the Kinect sensor is used in this paper to determine the precise measurements. The two sets of feature are separately tested and then fused to create one feature vector. A database has been created in house to perform our experiments. This database consists of sixteen males and four females. For each individual, 10 videos have been recorded, each record includes in average two gait cycles. The Kinect sensor is used here to extract all the skeleton points, and these points are used to build up the feature vectors mentioned above. K-nearest neighbor is used as the classification method based on Cityblock distance function. Based on the experimental result the proposed method provides 56% as a recognition rate using HDF, while VDF provided 83.5% recognition accuracy. When fusing both of the HDF and VDF as one feature vector, the recognition rate increased to 92%, the experimental result shows that our method provides significant result compared to the existence methods.

  19. Automatic target recognition on the connection machine

    SciTech Connect

    Buchanan, J.R. )

    1989-09-01

    Automatic target recognition (ATR) is a computationally intensive problem that benefits from the abilities of the Connection Machine (CM), a massively parallel computer used for data-level parallel computing. The large computational resources of the CM can efficiently handle an approach to ATR that uses parallel stereo-matching and neural-network algorithms. Such an approach shows promise as an ATR system of satisfactory performance. 13 refs.

  20. Speech recognition in natural background noise.

    PubMed

    Meyer, Julien; Dentel, Laure; Meunier, Fanny

    2013-01-01

    In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (-8.8 dB to -18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies

  1. Shape Representation And Recognition With Depth Information

    NASA Astrophysics Data System (ADS)

    Gorman, John W.; Mitchell, O. Robert

    1988-02-01

    Many global shape recognition techniques, such as moments and Fourier Descriptors, are used almost exclusively with two-dimensional images. It would be desirable to extend these global shape recognition concepts to three dimensional images. Specifically, the concepts associated with Fourier Descriptors will be extended to both three dimensional object representation and recognition and the representation and recognition of objects which are described by depth data. With Fourier Descriptors, two dimensional shape boundaries are described in terms of a set of complex sinusoidal basis functions. Extending this concept to three dimensions, the surface of a shape will be described in terms of a set of three .dimensional basis functions. The basis functions which will be used are known as spherical harmonics. Spherical harmonics can be used to describe a function on the surface of the unit sphere. In this application, the function on the unit sphere will describe the shape to be represented. The representation presented here is restricted to the class of objects for which each ray from the origin intersects the surface of the object only once. Basic definitions and properties of spherical harmonics will be discussed. A distance measure for shape discrimination will be derived as a function of the spherical harmonic coefficients for two shapes. The question of representation of objects described by depth data will then be addressed. A functional description for the objects will be introduced, along with methods of normalizing the spherical harmonic coefficients for scale, translation, and orientation so that meaningful library comparisons might be possible. Classification results obtained with a set of simple objects will be discussed.

  2. Speech Recognition in Natural Background Noise

    PubMed Central

    Meyer, Julien; Dentel, Laure; Meunier, Fanny

    2013-01-01

    In the real world, human speech recognition nearly always involves listening in background noise. The impact of such noise on speech signals and on intelligibility performance increases with the separation of the listener from the speaker. The present behavioral experiment provides an overview of the effects of such acoustic disturbances on speech perception in conditions approaching ecologically valid contexts. We analysed the intelligibility loss in spoken word lists with increasing listener-to-speaker distance in a typical low-level natural background noise. The noise was combined with the simple spherical amplitude attenuation due to distance, basically changing the signal-to-noise ratio (SNR). Therefore, our study draws attention to some of the most basic environmental constraints that have pervaded spoken communication throughout human history. We evaluated the ability of native French participants to recognize French monosyllabic words (spoken at 65.3 dB(A), reference at 1 meter) at distances between 11 to 33 meters, which corresponded to the SNRs most revealing of the progressive effect of the selected natural noise (−8.8 dB to −18.4 dB). Our results showed that in such conditions, identity of vowels is mostly preserved, with the striking peculiarity of the absence of confusion in vowels. The results also confirmed the functional role of consonants during lexical identification. The extensive analysis of recognition scores, confusion patterns and associated acoustic cues revealed that sonorant, sibilant and burst properties were the most important parameters influencing phoneme recognition. . Altogether these analyses allowed us to extract a resistance scale from consonant recognition scores. We also identified specific perceptual consonant confusion groups depending of the place in the words (onset vs. coda). Finally our data suggested that listeners may access some acoustic cues of the CV transition, opening interesting perspectives for future studies

  3. Towards automatic musical instrument timbre recognition

    NASA Astrophysics Data System (ADS)

    Park, Tae Hong

    This dissertation is comprised of two parts---focus on issues concerning research and development of an artificial system for automatic musical instrument timbre recognition and musical compositions. The technical part of the essay includes a detailed record of developed and implemented algorithms for feature extraction and pattern recognition. A review of existing literature introducing historical aspects surrounding timbre research, problems associated with a number of timbre definitions, and highlights of selected research activities that have had significant impact in this field are also included. The developed timbre recognition system follows a bottom-up, data-driven model that includes a pre-processing module, feature extraction module, and a RBF/EBF (Radial/Elliptical Basis Function) neural network-based pattern recognition module. 829 monophonic samples from 12 instruments have been chosen from the Peter Siedlaczek library (Best Service) and other samples from the Internet and personal collections. Significant emphasis has been put on feature extraction development and testing to achieve robust and consistent feature vectors that are eventually passed to the neural network module. In order to avoid a garbage-in-garbage-out (GIGO) trap and improve generality, extra care was taken in designing and testing the developed algorithms using various dynamics, different playing techniques, and a variety of pitches for each instrument with inclusion of attack and steady-state portions of a signal. Most of the research and development was conducted in Matlab. The compositional part of the essay includes brief introductions to "A d'Ess Are ," "Aboji," "48 13 N, 16 20 O," and "pH-SQ." A general outline pertaining to the ideas and concepts behind the architectural designs of the pieces including formal structures, time structures, orchestration methods, and pitch structures are also presented.

  4. VLSI Microsystem for Rapid Bioinformatic Pattern Recognition

    NASA Technical Reports Server (NTRS)

    Fang, Wai-Chi; Lue, Jaw-Chyng

    2009-01-01

    A system comprising very-large-scale integrated (VLSI) circuits is being developed as a means of bioinformatics-oriented analysis and recognition of patterns of fluorescence generated in a microarray in an advanced, highly miniaturized, portable genetic-expression-assay instrument. Such an instrument implements an on-chip combination of polymerase chain reactions and electrochemical transduction for amplification and detection of deoxyribonucleic acid (DNA).

  5. Mapping the development of facial expression recognition.

    PubMed

    Rodger, Helen; Vizioli, Luca; Ouyang, Xinyi; Caldara, Roberto

    2015-11-01

    Reading the non-verbal cues from faces to infer the emotional states of others is central to our daily social interactions from very early in life. Despite the relatively well-documented ontogeny of facial expression recognition in infancy, our understanding of the development of this critical social skill throughout childhood into adulthood remains limited. To this end, using a psychophysical approach we implemented the QUEST threshold-seeking algorithm to parametrically manipulate the quantity of signals available in faces normalized for contrast and luminance displaying the six emotional expressions, plus neutral. We thus determined observers' perceptual thresholds for effective discrimination of each emotional expression from 5 years of age up to adulthood. Consistent with previous studies, happiness was most easily recognized with minimum signals (35% on average), whereas fear required the maximum signals (97% on average) across groups. Overall, recognition improved with age for all expressions except happiness and fear, for which all age groups including the youngest remained within the adult range. Uniquely, our findings characterize the recognition trajectories of the six basic emotions into three distinct groupings: expressions that show a steep improvement with age - disgust, neutral, and anger; expressions that show a more gradual improvement with age - sadness, surprise; and those that remain stable from early childhood - happiness and fear, indicating that the coding for these expressions is already mature by 5 years of age. Altogether, our data provide for the first time a fine-grained mapping of the development of facial expression recognition. This approach significantly increases our understanding of the decoding of emotions across development and offers a novel tool to measure impairments for specific facial expressions in developmental clinical populations. PMID:25704672

  6. Securing iris recognition systems against masquerade attacks

    NASA Astrophysics Data System (ADS)

    Galbally, Javier; Gomez-Barrero, Marta; Ross, Arun; Fierrez, Julian; Ortega-Garcia, Javier

    2013-05-01

    A novel two-stage protection scheme for automatic iris recognition systems against masquerade attacks carried out with synthetically reconstructed iris images is presented. The method uses different characteristics of real iris images to differentiate them from the synthetic ones, thereby addressing important security flaws detected in state-of-the-art commercial systems. Experiments are carried out on the publicly available Biosecure Database and demonstrate the efficacy of the proposed security enhancing approach.

  7. Video face recognition against a watch list

    NASA Astrophysics Data System (ADS)

    Abbas, Jehanzeb; Dagli, Charlie K.; Huang, Thomas S.

    2007-10-01

    Due to a large increase in the video surveillance data recently in an effort to maintain high security at public places, we need more robust systems to analyze this data and make tasks like face recognition a realistic possibility in challenging environments. In this paper we explore a watch-list scenario where we use an appearance based model to classify query faces from low resolution videos into either a watch-list or a non-watch-list face. We then use our simple yet a powerful face recognition system to recognize the faces classified as watch-list faces. Where the watch-list includes those people that we are interested in recognizing. Our system uses simple feature machine algorithms from our previous work to match video faces against still images. To test our approach, we match video faces against a large database of still images obtained from a previous work in the field from Yahoo News over a period of time. We do this matching in an efficient manner to come up with a faster and nearly real-time system. This system can be incorporated into a larger surveillance system equipped with advanced algorithms involving anomalous event detection and activity recognition. This is a step towards more secure and robust surveillance systems and efficient video data analysis.

  8. Making Activity Recognition Robust against Deceptive Behavior

    PubMed Central

    Saeb, Sohrab; Körding, Konrad; Mohr, David C.

    2015-01-01

    Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shaking the phone while seated to make the classifier detect walking. If they succeeded, we used their motion data to retrain the classifier, and asked them to try to trick it again. The experiment ended when subjects could no longer cheat. We found that some subjects were not able to trick the classifier at all, while others required five rounds of retraining. While classifiers trained on normal activity data predicted true activity with ~38% accuracy, training on the data gathered during the deceptive behavior increased their accuracy to ~84%. We conclude that learning the deceptive behavior of one individual helps to detect the deceptive behavior of others. Thus, we can make current activity recognition robust to deception by including deceptive activity data from a few individuals. PMID:26659118

  9. Flexible Parts-based Sketch Recognition

    NASA Astrophysics Data System (ADS)

    van de Panne, Michiel; Sharon, Dana

    Drawings and sketches are a natural way for people to communicate ideas, but it remains challenging to develop automated systems that can robustly recognize and interpret what is drawn. Most commonly, a drawing is first processed to obtain a low-level representation of that drawing in terms of lines or strokes, and this representation is then searched for matches to known object templates. In this chapter we propose two template-based methods for sketch recognition. A novel feature of these methods is that they both employ a hierarchy-of-parts template model that provides explicit support for templates with optional parts. This captures significant parts-based variation which would otherwise require a multitude of fixed-structure templates to model. The first method is developed for recognition in drawings consisting of sets of connected strokes and is applied as an interface for creating 3D models of airplanes, mugs, and fish. The second method allows for the recognition of more unstructured objects such as faces, plants, and sailboats in drawings that may also contain disjoint strokes. Neither method relies on the timing information of the input strokes, which may not be available for photographed or scanned drawings.

  10. Multimodal approaches for emotion recognition: a survey

    NASA Astrophysics Data System (ADS)

    Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

    2004-12-01

    Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

  11. Multimodal approaches for emotion recognition: a survey

    NASA Astrophysics Data System (ADS)

    Sebe, Nicu; Cohen, Ira; Gevers, Theo; Huang, Thomas S.

    2005-01-01

    Recent technological advances have enabled human users to interact with computers in ways previously unimaginable. Beyond the confines of the keyboard and mouse, new modalities for human-computer interaction such as voice, gesture, and force-feedback are emerging. Despite important advances, one necessary ingredient for natural interaction is still missing-emotions. Emotions play an important role in human-to-human communication and interaction, allowing people to express themselves beyond the verbal domain. The ability to understand human emotions is desirable for the computer in several applications. This paper explores new ways of human-computer interaction that enable the computer to be more aware of the user's emotional and attentional expressions. We present the basic research in the field and the recent advances into the emotion recognition from facial, voice, and physiological signals, where the different modalities are treated independently. We then describe the challenging problem of multimodal emotion recognition and we advocate the use of probabilistic graphical models when fusing the different modalities. We also discuss the difficult issues of obtaining reliable affective data, obtaining ground truth for emotion recognition, and the use of unlabeled data.

  12. Emotion recognition in girls with conduct problems.

    PubMed

    Schwenck, Christina; Gensthaler, Angelika; Romanos, Marcel; Freitag, Christine M; Schneider, Wolfgang; Taurines, Regina

    2014-01-01

    A deficit in emotion recognition has been suggested to underlie conduct problems. Although several studies have been conducted on this topic so far, most concentrated on male participants. The aim of the current study was to compare recognition of morphed emotional faces in girls with conduct problems (CP) with elevated or low callous-unemotional (CU+ vs. CU-) traits and a matched healthy developing control group (CG). Sixteen girls with CP-CU+, 16 girls with CP-CU- and 32 controls (mean age: 13.23 years, SD=2.33 years) were included. Video clips with morphed faces were presented in two runs to assess emotion recognition. Multivariate analysis of variance with the factors group and run was performed. Girls with CP-CU- needed more time than the CG to encode sad, fearful, and happy faces and they correctly identified sadness less often. Girls with CP-CU+ outperformed the other groups in the identification of fear. Learning effects throughout runs were the same for all groups except that girls with CP-CU- correctly identified fear less often in the second run compared to the first run. Results need to be replicated with comparable tasks, which might result in subgroup-specific therapeutic recommendations. PMID:23568422

  13. Cross-domain human action recognition.

    PubMed

    Bian, Wei; Tao, Dacheng; Rui, Yong

    2012-04-01

    Conventional human action recognition algorithms cannot work well when the amount of training videos is insufficient. We solve this problem by proposing a transfer topic model (TTM), which utilizes information extracted from videos in the auxiliary domain to assist recognition tasks in the target domain. The TTM is well characterized by two aspects: 1) it uses the bag-of-words model trained from the auxiliary domain to represent videos in the target domain; and 2) it assumes each human action is a mixture of a set of topics and uses the topics learned from the auxiliary domain to regularize the topic estimation in the target domain, wherein the regularization is the summation of Kullback-Leibler divergences between topic pairs of the two domains. The utilization of the auxiliary domain knowledge improves the generalization ability of the learned topic model. Experiments on Weizmann and KTH human action databases suggest the effectiveness of the proposed TTM for cross-domain human action recognition. PMID:21954214

  14. Automatic Speech Recognition Based on Electromyographic Biosignals

    NASA Astrophysics Data System (ADS)

    Jou, Szu-Chen Stan; Schultz, Tanja

    This paper presents our studies of automatic speech recognition based on electromyographic biosignals captured from the articulatory muscles in the face using surface electrodes. We develop a phone-based speech recognizer and describe how the performance of this recognizer improves by carefully designing and tailoring the extraction of relevant speech feature toward electromyographic signals. Our experimental design includes the collection of audibly spoken speech simultaneously recorded as acoustic data using a close-speaking microphone and as electromyographic signals using electrodes. Our experiments indicate that electromyographic signals precede the acoustic signal by about 0.05-0.06 seconds. Furthermore, we introduce articulatory feature classifiers, which had recently shown to improved classical speech recognition significantly. We describe that the classification accuracy of articulatory features clearly benefits from the tailored feature extraction. Finally, these classifiers are integrated into the overall decoding framework applying a stream architecture. Our final system achieves a word error rate of 29.9% on a 100-word recognition task.

  15. Personal recognition using hand shape and texture.

    PubMed

    Kumar, Ajay; Zhang, David

    2006-08-01

    This paper proposes a new bimodal biometric system using feature-level fusion of hand shape and palm texture. The proposed combination is of significance since both the palmprint and hand-shape images are proposed to be extracted from the single hand image acquired from a digital camera. Several new hand-shape features that can be used to represent the hand shape and improve the performance are investigated. The new approach for palmprint recognition using discrete cosine transform coefficients, which can be directly obtained from the camera hardware, is demonstrated. None of the prior work on hand-shape or palmprint recognition has given any attention on the critical issue of feature selection. Our experimental results demonstrate that while majority of palmprint or hand-shape features are useful in predicting the subjects identity, only a small subset of these features are necessary in practice for building an accurate model for identification. The comparison and combination of proposed features is evaluated on the diverse classification schemes; naive Bayes (normal, estimated, multinomial), decision trees (C4.5, LMT), k-NN, SVM, and FFN. Although more work remains to be done, our results to date indicate that the combination of selected hand-shape and palmprint features constitutes a promising addition to the biometrics-based personal recognition systems. PMID:16900698

  16. Genetic feature selection for gait recognition

    NASA Astrophysics Data System (ADS)

    Tafazzoli, Faezeh; Bebis, George; Louis, Sushil; Hussain, Muhammad

    2015-01-01

    Many research studies have demonstrated that gait can serve as a useful biometric modality for human identification at a distance. Traditional gait recognition systems, however, have mostly been evaluated without explicitly considering the most relevant gait features, which might have compromised performance. We investigate the problem of selecting a subset of the most relevant gait features for improving gait recognition performance. This is achieved by discarding redundant and irrelevant gait features while preserving the most informative ones. Motivated by our previous work on feature subset selection using genetic algorithms (GAs), we propose using GAs to select an optimal subset of gait features. First, features are extracted using kernel principal component analysis (KPCA) on spatiotemporal projections of gait silhouettes. Then, GA is applied to select a subset of eigenvectors in KPCA space that best represents a subject's identity. Each gait pattern is then represented by projecting it only on the eigenvectors selected by the GA. To evaluate the effectiveness of the selected features, we have experimented with two different classifiers: k nearest-neighbor and Naïve Bayes classifier. We report considerable gait recognition performance improvements on the Georgia Tech and CASIA databases.

  17. Success potential of automated star pattern recognition

    NASA Technical Reports Server (NTRS)

    Van Bezooijen, R. W. H.

    1986-01-01

    A quasi-analytical model is presented for calculating the success probability of automated star pattern recognition systems for attitude control of spacecraft. The star data is gathered by an imaging star tracker (STR) with a circular FOV capable of detecting 20 stars. The success potential is evaluated in terms of the equivalent diameters of the FOV and the target star area ('uniqueness area'). Recognition is carried out as a function of the position and brightness of selected stars in an area around each guide star. The success of the system is dependent on the resultant pointing error, and is calculated by generating a probability distribution of reaching a threshold probability of an unacceptable pointing error. The method yields data which are equivalent to data available with Monte Carlo simulatins. When applied to the recognition system intended for use on the Space IR Telescope Facility it is shown that acceptable pointing, to a level of nearly 100 percent certainty, can be obtained using a single star tracker and about 4000 guide stars.

  18. Picture recognition improves with subsequent verbal information.

    PubMed

    Wiseman, S; MacLeod, C M; Lootsteen, P J

    1985-07-01

    In three experiments, subjects studied photographs presented alone or followed by a descriptive sentence. The sentence provided additional information not available in the picture. Subsequent yes-no recognition tests for the pictures demonstrated better memory for those pictures that had been followed by descriptive sentences. Experiment 1 showed that described pictures were remembered better regardless of whether comparison was to undescribed pictures presented in immediate succession or to undescribed pictures followed by a blank period equal in duration to the descriptive sentence. Experiment 2 demonstrated that although both unrelated and related sentences aided picture recognition, related sentences were significantly more helpful. Experiment 3 revealed that increasing the amount of related information (low, medium, and high) had no differential effect on picture recognition. Three explanations of these results are considered: integration of the sentence with the picture, formation of a semantic representation in addition to the pictorial one, and elaboration of the pictorial representation initiated by the sentence. Taken together, the findings seem most consistent with the elaboration account--A post-picture sentence improves attention to and perhaps rehearsal of the representation of the picture following its display. PMID:3160818

  19. An online handwriting recognition system for Turkish

    NASA Astrophysics Data System (ADS)

    Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

    2005-01-01

    Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

  20. An online handwriting recognition system for Turkish

    NASA Astrophysics Data System (ADS)

    Vural, Esra; Erdogan, Hakan; Oflazer, Kemal; Yanikoglu, Berrin A.

    2004-12-01

    Despite recent developments in Tablet PC technology, there has not been any applications for recognizing handwritings in Turkish. In this paper, we present an online handwritten text recognition system for Turkish, developed using the Tablet PC interface. However, even though the system is developed for Turkish, the addressed issues are common to online handwriting recognition systems in general. Several dynamic features are extracted from the handwriting data for each recorded point and Hidden Markov Models (HMM) are used to train letter and word models. We experimented with using various features and HMM model topologies, and report on the effects of these experiments. We started with first and second derivatives of the x and y coordinates and relative change in the pen pressure as initial features. We found that using two more additional features, that is, number of neighboring points and relative heights of each point with respect to the base-line improve the recognition rate. In addition, extracting features within strokes and using a skipping state topology improve the system performance as well. The improved system performance is 94% in recognizing handwritten words from a 1000-word lexicon.

  1. Pattern Recognition in Pharmacokinetic Data Analysis.

    PubMed

    Gabrielsson, Johan; Meibohm, Bernd; Weiner, Daniel

    2016-01-01

    Pattern recognition is a key element in pharmacokinetic data analyses when first selecting a model to be regressed to data. We call this process going from data to insight and it is an important aspect of exploratory data analysis (EDA). But there are very few formal ways or strategies that scientists typically use when the experiment has been done and data collected. This report deals with identifying the properties of a kinetic model by dissecting the pattern that concentration-time data reveal. Pattern recognition is a pivotal activity when modeling kinetic data, because a rigorous strategy is essential for dissecting the determinants behind concentration-time courses. First, we extend a commonly used relationship for calculation of the number of potential model parameters by simultaneously utilizing all concentration-time courses. Then, a set of points to consider are proposed that specifically addresses exploratory data analyses, number of phases in the concentration-time course, baseline behavior, time delays, peak shifts with increasing doses, flip-flop phenomena, saturation, and other potential nonlinearities that an experienced eye catches in the data. Finally, we set up a series of equations related to the patterns. In other words, we look at what causes the shapes that make up the concentration-time course and propose a strategy to construct a model. By practicing pattern recognition, one can significantly improve the quality and timeliness of data analysis and model building. A consequence of this is a better understanding of the complete concentration-time profile. PMID:26338231

  2. Model attraction in medical image object recognition

    NASA Astrophysics Data System (ADS)

    Tascini, Guido; Zingaretti, Primo

    1995-04-01

    This paper presents as new approach to image recognition based on a general attraction principle. A cognitive recognition is governed by a 'focus on attention' process that concentrates on the visual data subset of task- relevant type only. Our model-based approach combines it with another process, focus on attraction, which concentrates on the transformations of visual data having relevance for the matching. The recognition process is characterized by an intentional evolution of the visual data. This chain of image transformations is viewed as driven by an attraction field that attempts to reduce the distance between the image-point and the model-point in the feature space. The field sources are determined during a learning phase, by supplying the system with a training set. The paper describes a medical interpretation case in the feature space, concerning human skin lesions. The samples of the training set, supplied by the dermatologists, allow the system to learn models of lesions in terms of features such as hue factor, asymmetry factor, and asperity factor. The comparison of the visual data with the model derives the trend of image transformations, allowing a better definition of the given image and its classification. The algorithms are implemented in C language on a PC equipped with Matrox Image Series IM-1280 acquisition and processing boards. The work is now in progress.

  3. Explanation mode for Bayesian automatic object recognition

    NASA Astrophysics Data System (ADS)

    Hazlett, Thomas L.; Cofer, Rufus H.; Brown, Harold K.

    1992-09-01

    One of the more useful techniques to emerge from AI is the provision of an explanation modality used by the researcher to understand and subsequently tune the reasoning of an expert system. Such a capability, missing in the arena of statistical object recognition, is not that difficult to provide. Long standing results show that the paradigm of Bayesian object recognition is truly optimal in a minimum probability of error sense. To a large degree, the Bayesian paradigm achieves optimality through adroit fusion of a wide range of lower informational data sources to give a higher quality decision--a very 'expert system' like capability. When various sources of incoming data are represented by C++ classes, it becomes possible to automatically backtrack the Bayesian data fusion process, assigning relative weights to the more significant datums and their combinations. A C++ object oriented engine is then able to synthesize 'English' like textural description of the Bayesian reasoning suitable for generalized presentation. Key concepts and examples are provided based on an actual object recognition problem.

  4. Biometric watermarking based on face recognition

    NASA Astrophysics Data System (ADS)

    Satonaka, Takami

    2002-04-01

    We describe biometric watermarking procedure based on object recognition for accurate facial signature authentication. An adaptive metric learning algorithm incorporating watermark and facial signatures is introduced to separate an arbitrary pattern of unknown intruder classes from that of known true-user ones. The verification rule of multiple signatures is formulated to map a facial signature pattern in the overlapping classes to a separable disjoint one. The watermark signature, which is uniquely assigned to each face image, reduces the uncertainty of modeling missing facial signature patterns of the unknown intruder classes. The adaptive metric learning algorithm proposed improves a recognition error rate from 2.4% to 0.07% using the ORL database, which is better than previously reported numbers using the Karhunen-Loeve transform, convolution network and the hidden Marcov model. The face recognition facilitates generation and distribution of the watermark key. The watermarking approach focuses on using salient facial features to make watermark signatures robust to various attacks and transformation. The coarse-to-fine approach is presented to integrate pyramidal face detection, geometry analysis and face segmentation for watermarking. We conclude with an assessment of the strength and weakness of the chosen approach as well as possible improvements of the biometric watermarking system.

  5. Aerial Scene Recognition using Efficient Sparse Representation

    SciTech Connect

    Cheriyadat, Anil M

    2012-01-01

    Advanced scene recognition systems for processing large volumes of high-resolution aerial image data are in great demand today. However, automated scene recognition remains a challenging problem. Efficient encoding and representation of spatial and structural patterns in the imagery are key in developing automated scene recognition algorithms. We describe an image representation approach that uses simple and computationally efficient sparse code computation to generate accurate features capable of producing excellent classification performance using linear SVM kernels. Our method exploits unlabeled low-level image feature measurements to learn a set of basis vectors. We project the low-level features onto the basis vectors and use simple soft threshold activation function to derive the sparse features. The proposed technique generates sparse features at a significantly lower computational cost than other methods~\\cite{Yang10, newsam11}, yet it produces comparable or better classification accuracy. We apply our technique to high-resolution aerial image datasets to quantify the aerial scene classification performance. We demonstrate that the dense feature extraction and representation methods are highly effective for automatic large-facility detection on wide area high-resolution aerial imagery.

  6. Effective acoustic modeling for robust speaker recognition

    NASA Astrophysics Data System (ADS)

    Hasan Al Banna, Taufiq

    Robustness due to mismatched train/test conditions is the biggest challenge facing the speaker recognition community today, with transmission channel and environmental noise degradation being the prominent factors. Performance of state-of-the art speaker recognition methods aim at mitigating these factors by effectively modeling speech in multiple recording conditions, so that it can learn to distinguish between inter-speaker and intra-speaker variability. The increasing demand and availability of large development corpora introduces difficulties in effective data utilization and computationally efficient modeling. Traditional compensation strategies operate on higher dimensional utterance features, known as supervectors, which are obtained from the acoustic modeling of short-time features. Feature compensation is performed during front-end processing. Motivated by the covariance structure of conventional acoustic features, we envision that feature normalization and compensation can be integrated into the acoustic modeling. In this dissertation, we investigate the following fundamental research challenges: (i) analysis of data requirements for effective and efficient background model training, (ii) introducing latent factor analysis modeling of acoustic features, (iii) integration of channel compensation strategies in mixture-models, and (iv) development of noise robust background models using factor analysis. The effectiveness of the proposed solutions are demonstrated in various noisy and channel degraded conditions using the recent evaluation datasets released by the National Institute of Standards and Technology (NIST). These research accomplishments make an important step towards improving speaker recognition robustness in diverse acoustic conditions.

  7. Emotion recognition from speech: tools and challenges

    NASA Astrophysics Data System (ADS)

    Al-Talabani, Abdulbasit; Sellahewa, Harin; Jassim, Sabah A.

    2015-05-01

    Human emotion recognition from speech is studied frequently for its importance in many applications, e.g. human-computer interaction. There is a wide diversity and non-agreement about the basic emotion or emotion-related states on one hand and about where the emotion related information lies in the speech signal on the other side. These diversities motivate our investigations into extracting Meta-features using the PCA approach, or using a non-adaptive random projection RP, which significantly reduce the large dimensional speech feature vectors that may contain a wide range of emotion related information. Subsets of Meta-features are fused to increase the performance of the recognition model that adopts the score-based LDC classifier. We shall demonstrate that our scheme outperform the state of the art results when tested on non-prompted databases or acted databases (i.e. when subjects act specific emotions while uttering a sentence). However, the huge gap between accuracy rates achieved on the different types of datasets of speech raises questions about the way emotions modulate the speech. In particular we shall argue that emotion recognition from speech should not be dealt with as a classification problem. We shall demonstrate the presence of a spectrum of different emotions in the same speech portion especially in the non-prompted data sets, which tends to be more "natural" than the acted datasets where the subjects attempt to suppress all but one emotion.

  8. Macromolecular recognition in the Protein Data Bank

    SciTech Connect

    Janin, Joël; Rodier, Francis; Chakrabarti, Pinak

    2007-01-01

    X-ray structures in the PDB illustrate both the specific recognition of two polypeptide chains in protein–protein complexes and dimeric proteins and their nonspecific interaction at crystal contacts. Crystal structures deposited in the Protein Data Bank illustrate the diversity of biological macromolecular recognition: transient interactions in protein–protein and protein–DNA complexes and permanent assemblies in homodimeric proteins. The geometric and physical chemical properties of the macromolecular interfaces that may govern the stability and specificity of recognition are explored in complexes and homodimers compared with crystal-packing interactions. It is found that crystal-packing interfaces are usually much smaller; they bury fewer atoms and are less tightly packed than in specific assemblies. Standard-size interfaces burying 1200–2000 Å{sup 2} of protein surface occur in protease–inhibitor and antigen–antibody complexes that assemble with little or no conformation changes. Short-lived electron-transfer complexes have small interfaces; the larger size of the interfaces observed in complexes involved in signal transduction and homodimers correlates with the presence of conformation changes, often implicated in biological function. Results of the CAPRI (critical assessment of predicted interactions) blind prediction experiment show that docking algorithms efficiently and accurately predict the mode of assembly of proteins that do not change conformation when they associate. They perform less well in the presence of large conformation changes and the experiment stimulates the development of novel procedures that can handle such changes.

  9. Face recognition: a model specific ability.

    PubMed

    Wilmer, Jeremy B; Germine, Laura T; Nakayama, Ken

    2014-01-01

    In our everyday lives, we view it as a matter of course that different people are good at different things. It can be surprising, in this context, to learn that most of what is known about cognitive ability variation across individuals concerns the broadest of all cognitive abilities; an ability referred to as general intelligence, general mental ability, or just g. In contrast, our knowledge of specific abilities, those that correlate little with g, is severely constrained. Here, we draw upon our experience investigating an exceptionally specific ability, face recognition, to make the case that many specific abilities could easily have been missed. In making this case, we derive key insights from earlier false starts in the measurement of face recognition's variation across individuals, and we highlight the convergence of factors that enabled the recent discovery that this variation is specific. We propose that the case of face recognition ability illustrates a set of tools and perspectives that could accelerate fruitful work on specific cognitive abilities. By revealing relatively independent dimensions of human ability, such work would enhance our capacity to understand the uniqueness of individual minds. PMID:25346673

  10. Human body contour data based activity recognition.

    PubMed

    Myagmarbayar, Nergui; Yuki, Yoshida; Imamoglu, Nevrez; Gonzalez, Jose; Otake, Mihoko; Yu, Wenwei

    2013-01-01

    This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate. PMID:24111015

  11. Children's recognition of emotions from vocal cues.

    PubMed

    Sauter, Disa A; Panattoni, Charlotte; Happé, Francesca

    2013-03-01

    Emotional cues contain important information about the intentions and feelings of others. Despite a wealth of research into children's understanding of facial signals of emotions, little research has investigated the developmental trajectory of interpreting affective cues in the voice. In this study, 48 children ranging between 5 and 10 years were tested using forced-choice tasks with non-verbal vocalizations and emotionally inflected speech expressing different positive, neutral and negative states. Children as young as 5 years were proficient in interpreting a range of emotional cues from vocal signals. Consistent with previous work, performance was found to improve with age. Furthermore, the two tasks, examining recognition of non-verbal vocalizations and emotionally inflected speech, respectively, were sensitive to individual differences, with high correspondence of performance across the tasks. From this demonstration of children's ability to recognize emotions from vocal stimuli, we also conclude that this auditory emotion recognition task is suitable for a wide age range of children, providing a novel, empirical way to investigate children's affect recognition skills. PMID:23331109

  12. Neuromagnetic activity during recognition of emotional pictures.

    PubMed

    Kissler, Johanna; Hauswald, Anne

    2008-06-01

    Recently studied 'old' stimuli lead to larger frontal and parietal ERP responses than 'new' stimuli. The present experiment investigated the neuromagnetic correlates (MEG) of this 'old-new' effect and its modulation by emotional stimulus content. Highly arousing pleasant, highly arousing unpleasant and un-arousing neutral photographs were presented to the participants with the instruction to memorize them. They were later re-presented together with new photographs in an old-new decision task. In line with previous ERP studies, a long-lasting old-new effect (350-700 ms) was found. Independently, an emotion effect also occurred, as reflected in a, particularly left temporal, activity increase for emotional pictures between 450 and 580 ms. Moreover, only for the pleasant pictures did the early part of the old-new effect, which is thought to reflect familiarity based recognition processes, interact with picture content: The old-new effect for pleasant pictures in frontal regions was larger than the one for neutral or unpleasant pictures between 350 and 450 ms. In parallel, subjects' responses were accelerated towards and biased in favour of classifying pleasant pictures as old. However, when false alarm rate was taken into account, there was no significant effect of emotional content on recognition accuracy. In sum, this MEG study demonstrates an effect of particularly pleasant emotional content on recognition memory which may be mediated by a familiarity based process. PMID:18335310

  13. Peptidoglycan recognition by the Drosophila Imd pathway.

    PubMed

    Kaneko, Takashi; Golenbock, Douglas; Silverman, Neal

    2005-01-01

    The structural requirements for recognition of peptidoglycan (PGN) by PGRP-LC and activation of the Drosophila IMD pathway are not yet clear. In order to examine this question more carefully, the activity of peptidoglycan from different types of bacteria was compared in cell-based and whole animal assays. Drosophila S2* cells, but not adult flies, responded to Lys-type Micrococcus luteus PGN, but with significantly less potency compared to Dap-type Escherichia coli PGN, while intact Lys-type PGN from Staphylococcus aureus was inactive. After treatment with lysostaphin, which digests the cross-bridging peptides, S. aureus PGN weakly stimulated the IMD pathway, similar to M. luteus PGN. Further digestion with mutanolysin, which creates monomeric PGN fragments, abolished the activity of S. aureus PGN. On the other hand, monomeric E. coli PGN, generated by mutanolysin digestion, was still active but required different isoforms of PGRP-LC for recognition. Polymeric PGN required only PGRP-LCx, while monomeric E. coli PGN required both the PGRP-LCa and PGRP-LCx isoforms. These results suggest that the recognition by PGRP-LCx alone requires polymeric PGN, and that polymeric Dap-type PGN is a more potent PGRP-LCx agonist, compared to Lys-type PGN. These results also suggest that the heteromeric PGRP-LCa/LCx receptor complex recognizes monomeric Dap-type, but not Lys-type, PGN. PMID:16303095

  14. Activity Recognition on Streaming Sensor Data

    PubMed Central

    Krishnan, Narayanan C; Cook, Diane J

    2012-01-01

    Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition. PMID:24729780

  15. Making Activity Recognition Robust against Deceptive Behavior.

    PubMed

    Saeb, Sohrab; Körding, Konrad; Mohr, David C

    2015-01-01

    Healthcare services increasingly use the activity recognition technology to track the daily activities of individuals. In some cases, this is used to provide incentives. For example, some health insurance companies offer discount to customers who are physically active, based on the data collected from their activity tracking devices. Therefore, there is an increasing motivation for individuals to cheat, by making activity trackers detect activities that increase their benefits rather than the ones they actually do. In this study, we used a novel method to make activity recognition robust against deceptive behavior. We asked 14 subjects to attempt to trick our smartphone-based activity classifier by making it detect an activity other than the one they actually performed, for example by shaking the phone while seated to make the classifier detect walking. If they succeeded, we used their motion data to retrain the classifier, and asked them to try to trick it again. The experiment ended when subjects could no longer cheat. We found that some subjects were not able to trick the classifier at all, while others required five rounds of retraining. While classifiers trained on normal activity data predicted true activity with ~38% accuracy, training on the data gathered during the deceptive behavior increased their accuracy to ~84%. We conclude that learning the deceptive behavior of one individual helps to detect the deceptive behavior of others. Thus, we can make current activity recognition robust to deception by including deceptive activity data from a few individuals. PMID:26659118

  16. Privacy protection schemes for fingerprint recognition systems

    NASA Astrophysics Data System (ADS)

    Marasco, Emanuela; Cukic, Bojan

    2015-05-01

    The deployment of fingerprint recognition systems has always raised concerns related to personal privacy. A fingerprint is permanently associated with an individual and, generally, it cannot be reset if compromised in one application. Given that fingerprints are not a secret, potential misuses besides personal recognition represent privacy threats and may lead to public distrust. Privacy mechanisms control access to personal information and limit the likelihood of intrusions. In this paper, image- and feature-level schemes for privacy protection in fingerprint recognition systems are reviewed. Storing only key features of a biometric signature can reduce the likelihood of biometric data being used for unintended purposes. In biometric cryptosystems and biometric-based key release, the biometric component verifies the identity of the user, while the cryptographic key protects the communication channel. Transformation-based approaches only a transformed version of the original biometric signature is stored. Different applications can use different transforms. Matching is performed in the transformed domain which enable the preservation of low error rates. Since such templates do not reveal information about individuals, they are referred to as cancelable templates. A compromised template can be re-issued using a different transform. At image-level, de-identification schemes can remove identifiers disclosed for objectives unrelated to the original purpose, while permitting other authorized uses of personal information. Fingerprint images can be de-identified by, for example, mixing fingerprints or removing gender signature. In both cases, degradation of matching performance is minimized.

  17. Activity Recognition on Streaming Sensor Data.

    PubMed

    Krishnan, Narayanan C; Cook, Diane J

    2014-02-01

    Many real-world applications that focus on addressing needs of a human, require information about the activities being performed by the human in real-time. While advances in pervasive computing have lead to the development of wireless and non-intrusive sensors that can capture the necessary activity information, current activity recognition approaches have so far experimented on either a scripted or pre-segmented sequence of sensor events related to activities. In this paper we propose and evaluate a sliding window based approach to perform activity recognition in an on line or streaming fashion; recognizing activities as and when new sensor events are recorded. To account for the fact that different activities can be best characterized by different window lengths of sensor events, we incorporate the time decay and mutual information based weighting of sensor events within a window. Additional contextual information in the form of the previous activity and the activity of the previous window is also appended to the feature describing a sensor window. The experiments conducted to evaluate these techniques on real-world smart home datasets suggests that combining mutual information based weighting of sensor events and adding past contextual information into the feature leads to best performance for streaming activity recognition. PMID:24729780

  18. Can soft biometric traits assist user recognition?

    NASA Astrophysics Data System (ADS)

    Jain, Anil K.; Dass, Sarat C.; Nandakumar, Karthik

    2004-08-01

    Biometrics is rapidly gaining acceptance as the technology that can meet the ever increasing need for security in critical applications. Biometric systems automatically recognize individuals based on their physiological and behavioral characteristics. Hence, the fundamental requirement of any biometric recognition system is a human trait having several desirable properties like universality, distinctiveness, permanence, collectability, acceptability, and resistance to circumvention. However, a human characteristic that possesses all these properties has not yet been identified. As a result, none of the existing biometric systems provide perfect recognition and there is a scope for improving the performance of these systems. Although characteristics like gender, ethnicity, age, height, weight and eye color are not unique and reliable, they provide some information about the user. We refer to these characteristics as "soft" biometric traits and argue that these traits can complement the identity information provided by the primary biometric identifiers like fingerprint and face. This paper presents the motivation for utilizing soft biometric information and analyzes how the soft biometric traits can be automatically extracted and incorporated in the decision making process of the primary biometric system. Preliminary experiments were conducted on a fingerprint database of 160 users by synthetically generating soft biometric traits like gender, ethnicity, and height based on known statistics. The results show that the use of additional soft biometric user information significantly improves (approximately 6%) the recognition performance of the fingerprint biometric system.

  19. Restoration and recognition of distant, blurry irises.

    PubMed

    Stoker, David S; Wedd, Jonathan; Lavelle, Eric; van der Laan, Jan

    2013-03-20

    Raw iris images collected outdoors at standoff distances exceeding 25 m are susceptible to noise and atmospheric blur and even under ideal imaging conditions are too degraded to carry out recognition with high accuracy. Traditionally, atmospherically distorted images have been corrected through the use of unique hardware components such as adaptive optics. Here we apply a pure digital image restoration approach to correct for optical aberrations. Image restoration was applied to both single images and image sequences. We propose both a single-frame denoising and deblurring approach, and a multiframe fusion and deblurring approach. To compare performance of the proposed methods, iris recognitions were carried out using the approach of Daugman. Hamming distances (HDs) of computed binary iris codes were measured before and after the restoration. We found the HD decreased from >0.46 prior to a mean value of <0.39 for random single images. The multiframe fusion approach produced the most robust restoration and achieved a mean HD for all subjects in our data set of 0.33 while known false matches remained at 0.44. These results show that, when used properly, image restoration approaches do significantly increase recognition performance for known true positives with low increase in false positive detections, and irises can be recognized in turbulent atmospheric conditions. PMID:23518730

  20. Gait Recognition and Walking Exercise Intensity Estimation

    PubMed Central

    Lin, Bor-Shing; Liu, Yu-Ting; Yu, Chu; Jan, Gene Eu; Hsiao, Bo-Tang

    2014-01-01

    Cardiovascular patients consult doctors for advice regarding regular exercise, whereas obese patients must self-manage their weight. Because a system for permanently monitoring and tracking patients’ exercise intensities and workouts is necessary, a system for recognizing gait and estimating walking exercise intensity was proposed. For gait recognition analysis, αβ filters were used to improve the recognition of athletic attitude. Furthermore, empirical mode decomposition (EMD) was used to filter the noise of patients’ attitude to acquire the Fourier transform energy spectrum. Linear discriminant analysis was then applied to this energy spectrum for training and recognition. When the gait or motion was recognized, the walking exercise intensity was estimated. In addition, this study addressed the correlation between inertia and exercise intensity by using the residual function of the EMD and quadratic approximation to filter the effect of the baseline drift integral of the acceleration sensor. The increase in the determination coefficient of the regression equation from 0.55 to 0.81 proved that the accuracy of the method for estimating walking exercise intensity proposed by Kurihara was improved in this study. PMID:24714057

  1. A review of recent advances in 3D face recognition

    NASA Astrophysics Data System (ADS)

    Luo, Jing; Geng, Shuze; Xiao, Zhaoxia; Xiu, Chunbo

    2015-03-01

    Face recognition based on machine vision has achieved great advances and been widely used in the various fields. However, there are some challenges on the face recognition, such as facial pose, variations in illumination, and facial expression. So, this paper gives the recent advances in 3D face recognition. 3D face recognition approaches are categorized into four groups: minutiae approach, space transform approach, geometric features approach, model approach. Several typical approaches are compared in detail, including feature extraction, recognition algorithm, and the performance of the algorithm. Finally, this paper summarized the challenge existing in 3D face recognition and the future trend. This paper aims to help the researches majoring on face recognition.

  2. A smoothness constraint on the development of object recognition.

    PubMed

    Wood, Justin N

    2016-08-01

    Understanding how the brain learns to recognize objects is one of the ultimate goals in the cognitive sciences. To date, however, we have not yet characterized the environmental factors that cause object recognition to emerge in the newborn brain. Here, I present the results of a high-throughput controlled-rearing experiment that examined whether the development of object recognition requires experience with temporally smooth visual objects. When newborn chicks (Gallus gallus) were raised with virtual objects that moved smoothly over time, the chicks developed accurate color recognition, shape recognition, and color-shape binding abilities. In contrast, when newborn chicks were raised with virtual objects that moved non-smoothly over time, the chicks' object recognition abilities were severely impaired. These results provide evidence for a "smoothness constraint" on newborn object recognition. Experience with temporally smooth objects facilitates the development of object recognition. PMID:27208825

  3. Voice recognition: an enabling technology for modern health care?

    PubMed Central

    Bergeron, B. P.

    1996-01-01

    Recent performance breakthroughs in affordable, large vocabulary, speaker independent voice recognition systems have rekindled widespread interest in using voice recognition technology to enhance the palatability and effectiveness of clinician-mediated computing. However, even if industry fully addresses the formidable hardware requirements, less than perfect recognition accuracies, discrete voice recognition requirements, and throughput limitations, there are significant cognitive and implementation issues that must be adequately resolved before voice can become a ubiquitous input modality. Cognitive issues include making allowances for individual differences in verbal communication style and skill levels, the relative cognitive load of using a voice enabled interface compared to alternative modalities, and the user's cognitive style. Implementation issues include a significant training requirement, limited portability, lengthy user switching time, questionable privacy, satisfying hardware requirements and the suitability of voice recognition in specific work environments. The inevitable resolution of these issues coupled with continuously improving voice recognition performance, promises a new era for voice recognition in medicine. PMID:8947776

  4. Face and body recognition show similar improvement during childhood.

    PubMed

    Bank, Samantha; Rhodes, Gillian; Read, Ainsley; Jeffery, Linda

    2015-09-01

    Adults are proficient in extracting identity cues from faces. This proficiency develops slowly during childhood, with performance not reaching adult levels until adolescence. Bodies are similar to faces in that they convey identity cues and rely on specialized perceptual mechanisms. However, it is currently unclear whether body recognition mirrors the slow development of face recognition during childhood. Recent evidence suggests that body recognition develops faster than face recognition. Here we measured body and face recognition in 6- and 10-year-old children and adults to determine whether these two skills show different amounts of improvement during childhood. We found no evidence that they do. Face and body recognition showed similar improvement with age, and children, like adults, were better at recognizing faces than bodies. These results suggest that the mechanisms of face and body memory mature at a similar rate or that improvement of more general cognitive and perceptual skills underlies improvement of both face and body recognition. PMID:25909913

  5. Graded Effects of Social Conformity on Recognition Memory

    PubMed Central

    Axmacher, Nikolai; Gossen, Anna; Elger, Christian E.; Fell, Juergen

    2010-01-01

    Previous studies have shown that the opinion of confederates in a group influences recognition memory, but inconsistent results have been obtained concerning the question of whether recognition of items as old and new are affected similarly, possibly because only one or two confederates are present during the recognition phase. Here, we present data from a study where recognition of novel faces was tested in the presence of four confederates. In a long version of this experiment, recognition of items as old and new was similarly affected by group responses. However, in the short version, recognition of old items depended proportionally on the number of correct group responses, while rejection of new items only decreased significantly when all confederates gave an incorrect response. These findings indicate that differential effects of social conformity on recognition of items as old and new occur in situations with an intermediate level of group pressure. PMID:20174641

  6. Graded effects of social conformity on recognition memory.

    PubMed

    Axmacher, Nikolai; Gossen, Anna; Elger, Christian E; Fell, Juergen

    2010-01-01

    Previous studies have shown that the opinion of confederates in a group influences recognition memory, but inconsistent results have been obtained concerning the question of whether recognition of items as old and new are affected similarly, possibly because only one or two confederates are present during the recognition phase. Here, we present data from a study where recognition of novel faces was tested in the presence of four confederates. In a long version of this experiment, recognition of items as old and new was similarly affected by group responses. However, in the short version, recognition of old items depended proportionally on the number of correct group responses, while rejection of new items only decreased significantly when all confederates gave an incorrect response. These findings indicate that differential effects of social conformity on recognition of items as old and new occur in situations with an intermediate level of group pressure. PMID:20174641

  7. Analysis and Recognition of Curve Type as The Basis of Object Recognition in Image

    NASA Astrophysics Data System (ADS)

    Nugraha, Nurma; Madenda, Sarifuddin; Indarti, Dina; Dewi Agushinta, R.; pre="and">Ernastuti,

    2016-06-01

    An object in an image when analyzed further will show the characteristics that distinguish one object with another object in an image. Characteristics that are used in object recognition in an image can be a color, shape, pattern, texture and spatial information that can be used to represent objects in the digital image. The method has recently been developed for image feature extraction on objects that share characteristics curve analysis (simple curve) and use the search feature of chain code object. This study will develop an algorithm analysis and the recognition of the type of curve as the basis for object recognition in images, with proposing addition of complex curve characteristics with maximum four branches that will be used for the process of object recognition in images. Definition of complex curve is the curve that has a point of intersection. By using some of the image of the edge detection, the algorithm was able to do the analysis and recognition of complex curve shape well.

  8. Improving robustness of speech recognition systems

    NASA Astrophysics Data System (ADS)

    Mitra, Vikramjit

    2010-11-01

    Current Automatic Speech Recognition (ASR) systems fail to perform nearly as good as human speech recognition performance due to their lack of robustness against speech variability and noise contamination. The goal of this dissertation is to investigate these critical robustness issues, put forth different ways to address them and finally present an ASR architecture based upon these robustness criteria. Acoustic variations adversely affect the performance of current phone-based ASR systems, in which speech is modeled as 'beads-on-a-string', where the beads are the individual phone units. While phone units are distinctive in cognitive domain, they are varying in the physical domain and their variation occurs due to a combination of factors including speech style, speaking rate etc.; a phenomenon commonly known as 'coarticulation'. Traditional ASR systems address such coarticulatory variations by using contextualized phone-units such as triphones. Articulatory phonology accounts for coarticulatory variations by modeling speech as a constellation of constricting actions known as articulatory gestures. In such a framework, speech variations such as coarticulation and lenition are accounted for by gestural overlap in time and gestural reduction in space. To realize a gesture-based ASR system, articulatory gestures have to be inferred from the acoustic signal. At the initial stage of this research an initial study was performed using synthetically generated speech to obtain a proof-of-concept that articulatory gestures can indeed be recognized from the speech signal. It was observed that having vocal tract constriction trajectories (TVs) as intermediate representation facilitated the gesture recognition task from the speech signal. Presently no natural speech database contains articulatory gesture annotation; hence an automated iterative time-warping architecture is proposed that can annotate any natural speech database with articulatory gestures and TVs. Two natural

  9. Behavioral model of visual perception and recognition

    NASA Astrophysics Data System (ADS)

    Rybak, Ilya A.; Golovan, Alexander V.; Gusakova, Valentina I.

    1993-09-01

    In the processes of visual perception and recognition human eyes actively select essential information by way of successive fixations at the most informative points of the image. A behavioral program defining a scanpath of the image is formed at the stage of learning (object memorizing) and consists of sequential motor actions, which are shifts of attention from one to another point of fixation, and sensory signals expected to arrive in response to each shift of attention. In the modern view of the problem, invariant object recognition is provided by the following: (1) separated processing of `what' (object features) and `where' (spatial features) information at high levels of the visual system; (2) mechanisms of visual attention using `where' information; (3) representation of `what' information in an object-based frame of reference (OFR). However, most recent models of vision based on OFR have demonstrated the ability of invariant recognition of only simple objects like letters or binary objects without background, i.e. objects to which a frame of reference is easily attached. In contrast, we use not OFR, but a feature-based frame of reference (FFR), connected with the basic feature (edge) at the fixation point. This has provided for our model, the ability for invariant representation of complex objects in gray-level images, but demands realization of behavioral aspects of vision described above. The developed model contains a neural network subsystem of low-level vision which extracts a set of primary features (edges) in each fixation, and high- level subsystem consisting of `what' (Sensory Memory) and `where' (Motor Memory) modules. The resolution of primary features extraction decreases with distances from the point of fixation. FFR provides both the invariant representation of object features in Sensor Memory and shifts of attention in Motor Memory. Object recognition consists in successive recall (from Motor Memory) and execution of shifts of attention and

  10. A modular framework for biomedical concept recognition

    PubMed Central

    2013-01-01

    Background Concept recognition is an essential task in biomedical information extraction, presenting several complex and unsolved challenges. The development of such solutions is typically performed in an ad-hoc manner or using general information extraction frameworks, which are not optimized for the biomedical domain and normally require the integration of complex external libraries and/or the development of custom tools. Results This article presents Neji, an open source framework optimized for biomedical concept recognition built around four key characteristics: modularity, scalability, speed, and usability. It integrates modules for biomedical natural language processing, such as sentence splitting, tokenization, lemmatization, part-of-speech tagging, chunking and dependency parsing. Concept recognition is provided through dictionary matching and machine learning with normalization methods. Neji also integrates an innovative concept tree implementation, supporting overlapped concept names and respective disambiguation techniques. The most popular input and output formats, namely Pubmed XML, IeXML, CoNLL and A1, are also supported. On top of the built-in functionalities, developers and researchers can implement new processing modules or pipelines, or use the provided command-line interface tool to build their own solutions, applying the most appropriate techniques to identify heterogeneous biomedical concepts. Neji was evaluated against three gold standard corpora with heterogeneous biomedical concepts (CRAFT, AnEM and NCBI disease corpus), achieving high performance results on named entity recognition (F1-measure for overlap matching: species 95%, cell 92%, cellular components 83%, gene and proteins 76%, chemicals 65%, biological processes and molecular functions 63%, disorders 85%, and anatomical entities 82%) and on entity normalization (F1-measure for overlap name matching and correct identifier included in the returned list of identifiers: species 88

  11. Individual differences in involvement of the visual object recognition system during visual word recognition.

    PubMed

    Laszlo, Sarah; Sacchi, Elizabeth

    2015-01-01

    Individuals with dyslexia often evince reduced activation during reading in left hemisphere (LH) language regions. This can be observed along with increased activation in the right hemisphere (RH), especially in areas associated with object recognition - a pattern referred to as RH compensation. The mechanisms of RH compensation are relatively unclear. We hypothesize that RH compensation occurs when the RH object recognition system is called upon to supplement an underperforming LH visual word form recognition system. We tested this by collecting ERPs while participants with a range of reading abilities viewed words, objects, and word/object ambiguous items (e.g., "SMILE" shaped like a smile). Less experienced readers differentiate words, objects, and ambiguous items less strongly, especially over the RH. We suggest that this lack of differentiation may have negative consequences for dyslexic individuals demonstrating RH compensation. PMID:25957504

  12. Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

    PubMed Central

    Partila, Pavol; Voznak, Miroslav; Tovarek, Jaromir

    2015-01-01

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity of system computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlled systems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voice quality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accuracy and efficiency. PMID:26346654

  13. Using GOMS and Bayesian plan recognition to develop recognition models of operator behavior

    NASA Astrophysics Data System (ADS)

    Zaientz, Jack D.; DeKoven, Elyon; Piegdon, Nicholas; Wood, Scott D.; Huber, Marcus J.

    2006-05-01

    Trends in combat technology research point to an increasing role for uninhabited vehicles in modern warfare tactics. To support increased span of control over these vehicles human responsibilities need to be transformed from tedious, error-prone and cognition intensive operations into tasks that are more supervisory and manageable, even under intensely stressful conditions. The goal is to move away from only supporting human command of low-level system functions to intention-level human-system dialogue about the operator's tasks and situation. A critical element of this process is developing the means to identify when human operators need automated assistance and to identify what assistance they need. Toward this goal, we are developing an unmanned vehicle operator task recognition system that combines work in human behavior modeling and Bayesian plan recognition. Traditionally, human behavior models have been considered generative, meaning they describe all possible valid behaviors. Basing behavior recognition on models designed for behavior generation can offers advantages in improved model fidelity and reuse. It is not clear, however, how to reconcile the structural differences between behavior recognition and behavior modeling approaches. Our current work demonstrates that by pairing a cognitive psychology derived human behavior modeling approach, GOMS, with a Bayesian plan recognition engine, ASPRN, we can translate a behavior generation model into a recognition model. We will discuss the implications for using human performance models in this manner as well as suggest how this kind of modeling may be used to support the real-time control of multiple, uninhabited battlefield vehicles and other semi-autonomous systems.

  14. Post processing for offline Chinese handwritten character string recognition

    NASA Astrophysics Data System (ADS)

    Wang, YanWei; Ding, XiaoQing; Liu, ChangSong

    2012-01-01

    Offline Chinese handwritten character string recognition is one of the most important research fields in pattern recognition. Due to the free writing style, large variability in character shapes and different geometric characteristics, Chinese handwritten character string recognition is a challenging problem to deal with. However, among the current methods over-segmentation and merging method which integrates geometric information, character recognition information and contextual information, shows a promising result. It is found experimentally that a large part of errors are segmentation error and mainly occur around non-Chinese characters. In a Chinese character string, there are not only wide characters namely Chinese characters, but also narrow characters like digits and letters of the alphabet. The segmentation error is mainly caused by uniform geometric model imposed on all segmented candidate characters. To solve this problem, post processing is employed to improve recognition accuracy of narrow characters. On one hand, multi-geometric models are established for wide characters and narrow characters respectively. Under multi-geometric models narrow characters are not prone to be merged. On the other hand, top rank recognition results of candidate paths are integrated to boost final recognition of narrow characters. The post processing method is investigated on two datasets, in total 1405 handwritten address strings. The wide character recognition accuracy has been improved lightly and narrow character recognition accuracy has been increased up by 10.41% and 10.03% respectively. It indicates that the post processing method is effective to improve recognition accuracy of narrow characters.

  15. [Face recognition in patients with autism spectrum disorders].

    PubMed

    Kita, Yosuke; Inagaki, Masumi

    2012-07-01

    The present study aimed to review previous research conducted on face recognition in patients with autism spectrum disorders (ASD). Face recognition is a key question in the ASD research field because it can provide clues for elucidating the neural substrates responsible for the social impairment of these patients. Historically, behavioral studies have reported low performance and/or unique strategies of face recognition among ASD patients. However, the performance and strategy of ASD patients is comparable to those of the control group, depending on the experimental situation or developmental stage, suggesting that face recognition of ASD patients is not entirely impaired. Recent brain function studies, including event-related potential and functional magnetic resonance imaging studies, have investigated the cognitive process of face recognition in ASD patients, and revealed impaired function in the brain's neural network comprising the fusiform gyrus and amygdala. This impaired function is potentially involved in the diminished preference for faces, and in the atypical development of face recognition, eliciting symptoms of unstable behavioral characteristics in these patients. Additionally, face recognition in ASD patients is examined from a different perspective, namely self-face recognition, and facial emotion recognition. While the former topic is intimately linked to basic social abilities such as self-other discrimination, the latter is closely associated with mentalizing. Further research on face recognition in ASD patients should investigate the connection between behavioral and neurological specifics in these patients, by considering developmental changes and the spectrum clinical condition of ASD. PMID:22764354

  16. Spoken word recognition without a TRACE

    PubMed Central

    Hannagan, Thomas; Magnuson, James S.; Grainger, Jonathan

    2013-01-01

    How do we map the rapid input of spoken language onto phonological and lexical representations over time? Attempts at psychologically-tractable computational models of spoken word recognition tend either to ignore time or to transform the temporal input into a spatial representation. TRACE, a connectionist model with broad and deep coverage of speech perception and spoken word recognition phenomena, takes the latter approach, using exclusively time-specific units at every level of representation. TRACE reduplicates featural, phonemic, and lexical inputs at every time step in a large memory trace, with rich interconnections (excitatory forward and backward connections between levels and inhibitory links within levels). As the length of the memory trace is increased, or as the phoneme and lexical inventory of the model is increased to a realistic size, this reduplication of time- (temporal position) specific units leads to a dramatic proliferation of units and connections, begging the question of whether a more efficient approach is possible. Our starting point is the observation that models of visual object recognition—including visual word recognition—have grappled with the problem of spatial invariance, and arrived at solutions other than a fully-reduplicative strategy like that of TRACE. This inspires a new model of spoken word recognition that combines time-specific phoneme representations similar to those in TRACE with higher-level representations based on string kernels: temporally independent (time invariant) diphone and lexical units. This reduces the number of necessary units and connections by several orders of magnitude relative to TRACE. Critically, we compare the new model to TRACE on a set of key phenomena, demonstrating that the new model inherits much of the behavior of TRACE and that the drastic computational savings do not come at the cost of explanatory power. PMID:24058349

  17. Carbohydrate Recognition Properties of Human Ficolins

    PubMed Central

    Gout, Evelyne; Garlatti, Virginie; Smith, David F.; Lacroix, Monique; Dumestre-Pérard, Chantal; Lunardi, Thomas; Martin, Lydie; Cesbron, Jean-Yves; Arlaud, Gérard J.; Gaboriaud, Christine; Thielens, Nicole M.

    2010-01-01

    Ficolins are oligomeric innate immune recognition proteins consisting of a collagen-like region and a fibrinogen-like recognition domain that bind to pathogen- and apoptotic cell-associated molecular patterns. To investigate their carbohydrate binding specificities, serum-derived L-ficolin and recombinant H- and M-ficolins were fluorescently labeled, and their carbohydrate binding ability was analyzed by glycan array screening. L-ficolin preferentially recognized disulfated N-acetyllactosamine and tri- and tetrasaccharides containing terminal galactose or N-acetylglucosamine. Binding was sensitive to the position and orientation of the bond between N-acetyllactosamine and the adjacent carbohydrate. No significant binding of H-ficolin to any of the 377 glycans probed could be detected, providing further evidence for its poor lectin activity. M-ficolin bound preferentially to 9-O-acetylated 2-6-linked sialic acid derivatives and to various glycans containing sialic acid engaged in a 2-3 linkage. To further investigate the structural basis of sialic acid recognition by M-ficolin, point mutants were produced in which three residues of the fibrinogen domain were replaced by their counterparts in L-ficolin. Mutations G221F and A256V inhibited binding to the 9-O-acetylated sialic acid derivatives, whereas Y271F abolished interaction with all sialic acid-containing glycans. The crystal structure of the Y271F mutant fibrinogen domain was solved, showing that the mutation does not alter the structure of the ligand binding pocket. These analyses reveal novel ficolin ligands such as sulfated N-acetyllactosamine (L-ficolin) and gangliosides (M-ficolin) and provide precise insights into the sialic acid binding specificity of M-ficolin, emphasizing the essential role of Tyr271 in this respect. PMID:20032467

  18. Block error correction codes for face recognition

    NASA Astrophysics Data System (ADS)

    Hussein, Wafaa R.; Sellahewa, Harin; Jassim, Sabah A.

    2011-06-01

    Face recognition is one of the most desirable biometric-based authentication schemes to control access to sensitive information/locations and as a proof of identity to claim entitlement to services. The aim of this paper is to develop block-based mechanisms, to reduce recognition errors that result from varying illumination conditions with emphasis on using error correction codes. We investigate the modelling of error patterns in different parts/blocks of face images as a result of differences in illumination conditions, and we use appropriate error correction codes to deal with the corresponding distortion. We test the performance of our proposed schemes using the Extended Yale-B Face Database, which consists of face images belonging to 5 illumination subsets depending on the direction of light source from the camera. In our experiments each image is divided into three horizontal regions as follows: region1, three rows above the eyebrows, eyebrows and eyes; region2, nose region and region3, mouth and chin region. By estimating statistical parameters for errors in each region we select suitable BCH error correction codes that yield improved recognition accuracy for that particular region in comparison to applying error correction codes to the entire image. Discrete Wavelet Transform (DWT) to a depth of 3 is used for face feature extraction, followed by global/local binarization of coefficients in each subbands. We shall demonstrate that the use of BCH improves separation of the distribution of Hamming distances of client-client samples from the distribution of Hamming distances of imposter-client samples.

  19. Cataract influence on iris recognition performance

    NASA Astrophysics Data System (ADS)

    Trokielewicz, Mateusz; Czajka, Adam; Maciejewicz, Piotr

    2014-11-01

    This paper presents the experimental study revealing weaker performance of the automatic iris recognition methods for cataract-affected eyes when compared to healthy eyes. There is little research on the topic, mostly incorporating scarce databases that are often deficient in images representing more than one illness. We built our own database, acquiring 1288 eye images of 37 patients of the Medical University of Warsaw. Those images represent several common ocular diseases, such as cataract, along with less ordinary conditions, such as iris pattern alterations derived from illness or eye trauma. Images were captured in near-infrared light (used in biometrics) and for selected cases also in visible light (used in ophthalmological diagnosis). Since cataract is a disorder that is most populated by samples in the database, in this paper we focus solely on this illness. To assess the extent of the performance deterioration we use three iris recognition methodologies (commercial and academic solutions) to calculate genuine match scores for healthy eyes and those influenced by cataract. Results show a significant degradation in iris recognition reliability manifesting by worsening the genuine scores in all three matchers used in this study (12% of genuine score increase for an academic matcher, up to 175% of genuine score increase obtained for an example commercial matcher). This increase in genuine scores affected the final false non-match rate in two matchers. To our best knowledge this is the only study of such kind that employs more than one iris matcher, and analyzes the iris image segmentation as a potential source of decreased reliability

  20. Associative Pattern Recognition In Analog VLSI Circuits

    NASA Technical Reports Server (NTRS)

    Tawel, Raoul

    1995-01-01

    Winner-take-all circuit selects best-match stored pattern. Prototype cascadable very-large-scale integrated (VLSI) circuit chips built and tested to demonstrate concept of electronic associative pattern recognition. Based on low-power, sub-threshold analog complementary oxide/semiconductor (CMOS) VLSI circuitry, each chip can store 128 sets (vectors) of 16 analog values (vector components), vectors representing known patterns as diverse as spectra, histograms, graphs, or brightnesses of pixels in images. Chips exploit parallel nature of vector quantization architecture to implement highly parallel processing in relatively simple computational cells. Through collective action, cells classify input pattern in fraction of microsecond while consuming power of few microwatts.