Search results for "pattern"

showing 10 items of 4203 documents

Analysis of neuronal networks in the visual system of the cat using statistical signals--simple and complex cells. Part II.

1978

Superimposing additively a two-dimensional noise process to deterministic input signals (bars) the neurons of area 17 show a class-specific reaction for the task of signal extraction. Moving both parts of the signals simultaneously and varying the signal to noise ratio (S/N) the simple cells achieve the same performance as resulted from the psychophysical experiment. Type I complex cells extract moving deterministic signals (i.e. bars) from the stationary noise, whereas in the answers of Type II complex cells the statistical parts of the signals predominate. Considering the different cell types each as a series of a linear and a nonlinear system one obtains the cell specific space-time freq…

Cerebral CortexNeuronsGeneral Computer ScienceSeries (mathematics)Noise (signal processing)Computer scienceSpeech recognitionModels NeurologicalStatistics as TopicProcess (computing)Complex systemElectrophysiologyForm PerceptionNonlinear systemAmplitudeSignal-to-noise ratioPattern Recognition VisualSimple (abstract algebra)CatsAnimalsVisual PathwaysBiological systemMathematicsBiotechnologyBiological cybernetics
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Local symmetries of digital contours from their chain codes

1996

In this work symmetry is evaluated as a numeric feature for each point of a contour, using only the positions of a local vicinity of points. A measurement is defined, named as Local Symmetric Deficiency (LSD), so that the lower this quantity is, the higher the symmetry will be in the local region considered. This approach is very simple and it is based on a suitable manipulation of the chain code of the curve. Its computational cost is very low and it has the advantages of a parallel algorithm, since values for LSD can be computed for each point independently.

Chain codeFeature extractionParallel algorithmEdge detectionChain (algebraic topology)Artificial IntelligenceFeature (computer vision)Signal ProcessingPoint (geometry)Computer Vision and Pattern RecognitionSymmetry (geometry)AlgorithmSoftwareMathematicsPattern Recognition
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Modeling Multi-label Recurrence in Data Streams

2019

Most of the existing data stream algorithms assume a single label as the target variable. However, in many applications, each observation is assigned to several labels with latent dependencies among them, which their target function may change over time. Classification of such non-stationary multi-label streaming data with the consideration of dependencies among labels and potential drifts is a challenging task. The few existing studies mostly cope with drifts implicitly, and all learn models on the original label space, which requires a lot of time and memory. None of them consider recurrent drifts in multi-label streams and particularly drifts and recurrences visible in a latent label spa…

Change over timeMulti-label classificationData streambusiness.industryComputer scienceData stream miningSpace dimensionPattern recognitionComputingMethodologies_PATTERNRECOGNITIONStreaming dataArtificial intelligencebusinessClassifier (UML)Decoding methods2019 IEEE International Conference on Big Knowledge (ICBK)
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Variance Thresholded EMD-CCA Technique for Fast Eye Blink Artifacts Removal in EEG

2017

International audience; Eye blink (EB) artifacts generated during eye blinks often contaminate electroencephalogram (EEG) signal. Previously Empirical Mode Decomposition (EMD) and Canonical Correlation Analysis (CCA), hybrid EMD-CCA were developed for EB artifact removal in EEG. However, EMD restricts the hybrid algorithm for real time implementation due to its slow processing nature, hence the algorithm has to be enhanced so that it can be a viable solution for real-time EB artifact removal. In this research work, to avoid applying EMD repetitively as and when EB artifacts occur, a method to use EMD minimally is approached. A suitable EB artifact region is detected through a variance thres…

Channel (digital image)Computer scienceElectroencephalography[INFO] Computer Science [cs]Signal050105 experimental psychologyTime03 medical and health sciences0302 clinical medicineVariance ThresholdmedicineEMD0501 psychology and cognitive sciences[INFO]Computer Science [cs]EEGCCAArtifact (error)medicine.diagnostic_testEBbusiness.industry05 social sciencesOcular ArtifactPattern recognitionElectrooculographyFrequency-DomainRecordingsFrequency domainArtificial intelligencebusiness030217 neurology & neurosurgery
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Color encoding for polychromatic single-channel optical pattern recognition

2010

The common multichannel system for recognizing colored images is replaced by a color-encoded single-channel system. Amethod inspired by the Munsell color system is used for encoding the different colors as phase and amplitude functions. It is shown that for many practical cases the phase information part of the color code is sufficient for obtaining good results. An implementation based on a liquid-crystal television panel that works in a phase-modulation mode is suggested. Computer simulations that demonstrate the capabilities of the suggested method are given as well as a comparison with previously published multichannel performance.

Channel (digital image)Computer sciencebusiness.industryMaterials Science (miscellaneous)Pattern recognitionImage processingColor spaceIndustrial and Manufacturing EngineeringMunsell color systemEncoding (memory)Pattern recognition (psychology)Artificial intelligenceBusiness and International ManagementbusinessColor codeApplied Optics
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Nonlinear pattern recognition correlators based on color-encoding single-channel systems.

2004

In color pattern recognition, color channels are normally processed separately and afterward the correlation outputs are combined. This is the definition of multichannel processing. We combine a single-channel method with nonlinear filtering based on nonlinear correlations. These nonlinear correlations yield better discrimination than common matched filtering. The method codes color information as amplitude and phase distributions and is followed by correlations related to binary decompositions. The technique is based on binary decompositions of the red, green, and blue and the hue, saturation, and intensity monochromatic channels of the reference and of the input scene, after which the bin…

Channel (digital image)business.industryNoise (signal processing)Materials Science (miscellaneous)Pattern recognitionColor spaceIndustrial and Manufacturing EngineeringNonlinear systemOpticsPattern recognition (psychology)Monochromatic colorArtificial intelligenceBusiness and International ManagementbusinessLinear filterHueMathematicsApplied optics
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Ideal Chaotic Pattern Recognition is achievable: The Ideal-M-AdNN - its design and properties

2013

Published version of a chapter in the book: Transactions on Computational Collective Intelligence XI. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-41776-4_2 This paper deals with the relatively new field of designing a Chaotic Pattern Recognition (PR) system. The benchmark of such a system is the following: First of all, one must be able to train the system with a set of “training” patterns. Subsequently, as long as there is no testing pattern, the system must be chaotic. However, if the system is, thereafter, presented with an unknown testing pattern, the behavior must ideally be as follows. If the testing pattern is not one of the trained patterns, the system …

Chaotic Neural NetworksVDP::Mathematics and natural science: 400::Information and communication science: 420::Knowledge based systems: 425VDP::Technology: 500::Information and communication technology: 550Adachi-like Neural NetworksChaotic Pattern Recognition
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Micromechanical forces regulate vascular patterning in the chick chorioallantoic membrane (15.3)

2014

ChemistryGeneticsVascular patterningMolecular BiologyBiochemistryBiotechnologyChick chorioallantoic membraneCell biologyThe FASEB Journal
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Fingerprints from fingerprints

2003

Besides ‘‘classical’’ biological materials such as blood and sperm, epithelial cells from latent fingerprints are targeted in forensic sciences. In addition to studies using latent fingerprints applied to beer glasses [1], T-shirts left on crime scenes [2] and various other objects [3], we report the detection of STR profiles from latent fingerprints deposited on ordinary sheets of paper. In contrast to the relatively high number of epithelial cells from saliva or from excessively pressured fingerprints during strangulation [4,5], the experiments with latent fingerprints are expected to generate only a very small number of epithelial cells. Moreover, cells remaining on objects touched only …

Chemistrybusiness.industryFingerprint (computing)Pattern recognitionGeneral MedicineArtificial intelligencebusinessBiological materialsInternational Congress Series
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Evaluation of olfactory intensity : comparative study of two methods

2004

Two experimental procedures recommended for the evaluation of the psychophysical characteristics of odorous compounds, olfactory matching with the 1-butanol scale and cross-modality matching with the finger span are compared. The intensity of ethyl butyrate and guaiacol solutions presented at four different concentration levels was evaluated by a panel of sixteen subjects over five repetitions using the two methods. Each stimulus was delivered to the subject from a Teflon bag through a nose-shaped glass sniffing port. The discrimination ability, repeatability, panel homogeneity and within-subject variability of the methods were assessed. Results indicate that with both methods, subjects wer…

Chemistrybusiness.industry[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering010401 analytical chemistry05 social sciencesAnalytical chemistryPattern recognitionRepeatability[SDV.IDA] Life Sciences [q-bio]/Food engineering01 natural sciences050105 experimental psychologySensory Systems0104 chemical sciencesSniffingECARTEMENT DES DOIGTS[SDV.IDA]Life Sciences [q-bio]/Food engineering0501 psychology and cognitive sciences[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process EngineeringArtificial intelligencebusinessComputingMilieux_MISCELLANEOUSFood Science
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