Search results for "pattern"

showing 10 items of 4203 documents

Structured Output SVM for Remote Sensing Image Classification

2011

Traditional kernel classifiers assume independence among the classification outputs. As a consequence, each misclassification receives the same weight in the loss function. Moreover, the kernel function only takes into account the similarity between input values and ignores possible relationships between the classes to be predicted. These assumptions are not consistent for most of real-life problems. In the particular case of remote sensing data, this is not a good assumption either. Segmentation of images acquired by airborne or satellite sensors is a very active field of research in which one tries to classify a pixel into a predefined set of classes of interest (e.g. water, grass, trees,…

Computer scienceMultispectral imageTheoretical Computer ScienceSet (abstract data type)Kernel (linear algebra)One-class classificationRemote sensingSupport vector machinesStructured support vector machinePixelContextual image classificationbusiness.industryKernel methodsPattern recognitionLand use classificationSupport vector machineTree (data structure)Kernel methodHardware and ArchitectureControl and Systems EngineeringModeling and SimulationKernel (statistics)Radial basis function kernelSignal ProcessingStructured output learningArtificial intelligenceTree kernelStructured output learning; Support vector machines; Kernel methods; Land use classificationbusinessInformation SystemsJournal of Signal Processing Systems
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Quantitative evaluation of muscle synergy models: a single-trial task decoding approach.

2012

Delis, Ioannis | Berret, Bastien | Pozzo, Thierry | Panzeri, Stefano; International audience; ''Muscle synergies, i.e., invariant coordinated activations of groups of muscles, have been proposed as building blocks that the central nervous system (CNS) uses to construct the patterns of muscle activity utilized for executing movements . Several efficient dimensionality reduction algorithms that extract putative synergies from electromyographic (EMG) signals have been developed. Typically, the quality of synergy decompositions is assessed by computing the Variance Accounted For (VAF). Yet, little is known about the extent to which the combination of those synergies en codes task discriminating…

Computer scienceNeuroscience (miscellaneous)ORGANIZATIONMachine learningcomputer.software_genrelcsh:RC321-571Matrix decompositionNATURAL MOTOR BEHAVIORSFORCE03 medical and health sciencesCellular and Molecular NeurosciencePRIMITIVES0302 clinical medicinetask decodingmuscle synergiesMODULAR CONTROLMATRIX FACTORIZATIONOriginal Research ArticleMuscle activityInvariant (mathematics)Muscle synergylcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biologyARM MOVEMENTS0303 health sciencessingle-trial analysisarm movementbusiness.industryDimensionality reduction[SCCO.NEUR]Cognitive science/NeurosciencereachingTIME-VARYING SYNERGIES[ SCCO.NEUR ] Cognitive science/NeurosciencePATTERNS''NATURAL MOTOR BEHAVIORSArtificial intelligenceFORCE''Single trialSPINAL-CORDbusinesscomputer030217 neurology & neurosurgeryDecoding methodsNeuroscienceFrontiers in computational neuroscience
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''Investigating reduction of dimensionality during single-joint elbow movements: a case study on muscle synergies''

2013

Chiovetto, Enrico | Berret, Bastien | Delis, Ioannis | Panzeri, Stefano | Pozzo, Thierry; International audience; ''A long standing hypothesis in the neuroscience community is that the central nervous system (CNS) generates the muscle activities to accomplish movements by combining a relatively small number of stereotyped patterns of muscle activations, often referred to as" muscle synergies." Different definitions of synergies have been given in the literature. The most well-known are those of synchronous, time-varying and temporal muscle synergies. Each one of them is based on a different mathematical model used to factor some EMG array recordings collected during the execution of variety…

Computer scienceNeuroscience (miscellaneous)triphasic patternADJUSTMENTS''Variation (game tree)ORGANIZATIONTemporal musclelcsh:RC321-571NATURAL MOTOR BEHAVIORSnon-negative matrix factorizationACTIVATION03 medical and health sciencesCellular and Molecular Neuroscience0302 clinical medicineEMGEncoding (memory)muscle synergiesMATRIX FACTORIZATIONFeature (machine learning)Original Research ArticleSet (psychology)lcsh:Neurosciences. Biological psychiatry. Neuropsychiatry030304 developmental biologydimensionality reductionARM MOVEMENTSELECTROMYOGRAPHIC PATTERNS0303 health sciencesbusiness.industryDimensionality reductionCOMBINATIONS[SCCO.NEUR]Cognitive science/Neuroscienceelbow rotationsNeurophysiologyADJUSTMENTSBODY POINTING MOVEMENTS[ SCCO.NEUR ] Cognitive science/Neuroscience''NATURAL MOTOR BEHAVIORSArtificial intelligencebusiness030217 neurology & neurosurgeryCognitive psychologyCurse of dimensionalityNeuroscienceTRIPHASIC EMG PATTERN
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Automatic fringe pattern enhancement using truly adaptive period-guided bidimensional empirical mode decomposition.

2020

Fringe patterns encode the information about the result of a measurement performed via widely used optical full-field testing methods, e.g., interferometry, digital holographic microscopy, moiré techniques, structured illumination etc. Affected by the optical setup, changing environment and the sample itself fringe patterns are often corrupted with substantial noise, strong and uneven background illumination and exhibit low contrast. Fringe pattern enhancement, i.e., noise minimization and background term removal, at the pre-processing stage prior to the phase map calculation (for the measurement result decoding) is therefore essential to minimize the jeopardizing effect the mentioned error…

Computer sciencePhase contrast microscopyStructured illumination microscopy02 engineering and technology01 natural sciencesHilbert–Huang transformlaw.invention010309 opticsOpticslaw0103 physical sciencesbusiness.industrySignal reconstructionVDP::Technology: 500Moiré patternFilter (signal processing)021001 nanoscience & nanotechnologyAtomic and Molecular Physics and OpticsInterferometryVDP::Teknologi: 500Digital holographic microscopySpatial frequencySpeckle imaging0210 nano-technologybusinessAlgorithmOptics express
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Dynamic 3D Scene Reconstruction and Enhancement

2017

International audience; In this paper, we present a 3D reconstruction and enhancement approach for high quality dynamic city scene reconstructions. We first detect and segment the moving objects using 3D Motion Segmenta-tion approach by exploiting the feature trajectories' behaviours. Getting the segmentations of both the dynamic scene parts and the static scene parts, we propose an efficient point cloud registration approach which takes the advantages of 3-point RANSAC and Iterative Closest Points algorithms to produce precise point cloud alignment. Furthermore, we proposed a point cloud smoothing and texture mapping framework to enhance the results of reconstructions for both the static a…

Computer sciencePoint cloudComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingRANSACPoint Cloud Registration0202 electrical engineering electronic engineering information engineeringSegmentationComputer vision3D Scene Enhancement[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICSMotion Segmentationbusiness.industry3D reconstruction020207 software engineeringFeature (computer vision)Computer Science::Computer Vision and Pattern Recognition020201 artificial intelligence & image processingArtificial intelligencebusiness3D Reconstruction[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingTexture mappingSmoothing
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A blind mesh visual quality assessment method based on convolutional neural network

2018

International audience

Computer scienceQuality assessmentbusiness.industry[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingPattern recognition02 engineering and technology01 natural sciencesConvolutional neural network[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingArtificial intelligence010306 general physicsbusinessComputingMilieux_MISCELLANEOUS
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Reliability of Virtual Screening Methods in Prediction of PDE4Binhibitor Activity

2015

Identification of active ligands using computational methods is a challenging task. For example, molecular docking, pharmacophore modeling, and three dimensional quantitative structure-activity relationship models (3D-QSAR) are widely used methods to identify novel small molecules. However, all these methods have, in addition to advantages, also significant pitfalls. The aim of this study was to compare some commonly used computational methods to estimate their ability to separate highly active PDE4B-inhibitors from less active and inactive ones. Here, 152 molecules with pIC 50 -range of 3.4-10.5, originating from six original studies were used. High correlation coefficients by using dockin…

Computer scienceQuantitative Structure-Activity RelationshipMultiple methodsLigandsComputers MolecularDrug DiscoveryProtein Interaction MappingHumansSimulationPharmacological Phenomenathree-dimensional quantitative structure-activity relationshipVirtual screeningbusiness.industryta1182Pattern recognitionmolecular dockingmolecular mechanics-generalized born-surface areavirtual screeningCyclic Nucleotide Phosphodiesterases Type 4Molecular Docking SimulationDocking (molecular)pharmacophore modelingArtificial intelligencePhosphodiesterase 4 InhibitorsPharmacophorebusinessphosphodiesteraseCurrent Drug Discovery Technologies
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Special issue on architectures of smart cameras for real-time applications

2016

Smart cameras are embedded vision systems whose primary function is to produce a semantic understanding of the scene and generate a response in the form of application-specific signals and data. They are autonomous vision systems themselves and can be the building blocks of a more complex smart camera network. They are built around high-performance on-chip and on-board computing and communication infrastructure, combining image sensing, real-time image and video processing, and communications into a single embedded device. They can also be interconnected in networks and cooperate to provide access to many views, enabling more challenging applications in fields like visual control, surveilla…

Computer scienceReal-time computingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.TRON ] Engineering Sciences [physics]/Electronics[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI][SPI.TRON]Engineering Sciences [physics]/ElectronicsComputer graphics[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image ProcessingPattern recognition (psychology)Multimedia information systemsSmart camera[ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]ComputingMilieux_MISCELLANEOUSInformation SystemsJournal of Real-Time Image Processing
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A naive relevance feedback model for content-based image retrieval using multiple similarity measures

2010

This paper presents a novel probabilistic framework to process multiple sample queries in content based image retrieval (CBIR). This framework is independent from the underlying distance or (dis)similarity measures which support the retrieval system, and only assumes mutual independence among their outcomes. The proposed framework gives rise to a relevance feedback mechanism in which positive and negative data are combined in order to optimally retrieve images according to the available information. A particular setting in which users interactively supply feedback and iteratively retrieve images is set both to model the system and to perform some objective performance measures. Several repo…

Computer scienceRelevance feedbackContent-based image retrievalcomputer.software_genreSimilitudeSet (abstract data type)Similarity (network science)Artificial IntelligenceSignal ProcessingComputer Vision and Pattern RecognitionData miningImage retrievalcomputerSoftwareIndependence (probability theory)Pattern Recognition
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Steerable wavelet transform for atlas based retinal lesion segmentation

2013

International audience; Computer aided diagnosis and follow up can help in prevention and treatment of diabetes and its related complications. Screening of diabetes related disease in the eyes is done by a special low cost fundus camera. A follow up of the patients visiting at di fferent time intervals for screening brings us to the problem of image analysis for change detection and its cost per patient. It is very likely that human annotations for the lesions may be erroneous and often time consuming. Since the ethnic background plays a signi cant role in retinal pigment epithelium, visibility of the choroidal vasculature and overall retinal luminance in patients and retinal images, an eth…

Computer scienceRetinal lesionImage processing[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]LuminanceFundus camera030218 nuclear medicine & medical imaging03 medical and health scienceschemistry.chemical_compound0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]medicineSegmentationComputer visionRetinaRetinal pigment epitheliumDiabetic Retinopathybusiness.industryAtlas (topology)Atals segmentationWavelet transform[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseSteerable filtersmedicine.anatomical_structurechemistryComputer-aided diagnosis030221 ophthalmology & optometryRetinal ImageArtificial intelligencebusinessChange detection
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