Search results for "Pattern recognition"

showing 10 items of 2301 documents

The effect of wavelet and discrete cosine transform compression of digital radiographs on the detection of subtle proximal caries. ROC analysis.

2007

The study compared diagnostic performances of 2 different image compression methods: JPEG (discrete cosine transform; Joint Photographic Experts Group compression standard) versus JPEG2000 (discrete wavelet transform), both at a compression ratio of 12:1, from the original uncompressed TIFF radiograph with respect to the detection of non-cavitated carious lesions. Therefore, 100 approximal surfaces of 50 tooth pairs were evaluated on the radiographs by 10 experienced observers using a 5-point confidence scale. Observations were carried out on a standardized viewing monitor under subdued light conditions. The proportion of diseased surfaces was balanced to approximately 50% to avoid bias. Tr…

Discrete wavelet transformDental CariesSensitivity and SpecificityDiagnosis DifferentialWaveletComputer Science::MultimediaDiscrete cosine transformHumansDental EnamelGeneral DentistryLossless JPEGTransform codingMathematicsObserver VariationMicroscopybusiness.industryPattern recognitioncomputer.file_formatMicrotomyRadiography Dental DigitalData CompressionJPEGROC CurveJPEG 2000DentinArtificial intelligencebusinesscomputerAlgorithmsImage compressionCaries research
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Pattern recognition using sequential matched filtering of wavelet coefficients

1997

Abstract A bank of wavelets is used for pattern recognition by means of sequential filtering. Each element of the bank is matched to a different wavelet coefficient of the target. A sequential process leads to a set of correlation outputs. Post-processing by means of a fast blending method provides the final output correlation. Both computer simulations and optical experiments are presented, showing the discrimination capability for this implementation.

Discrete wavelet transformLifting schemeComputer sciencebusiness.industryStationary wavelet transformSecond-generation wavelet transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformCascade algorithmPattern recognitionFilter (signal processing)Atomic and Molecular Physics and OpticsElectronic Optical and Magnetic MaterialsWavelet packet decompositionWaveletArtificial intelligenceElectrical and Electronic EngineeringPhysical and Theoretical ChemistrybusinessContinuous wavelet transformOptics Communications
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Multiscale Edges Detection by Wavelet Transform for Model of Face Recognition

1996

Publisher Summary The linear auto-associator is a particular case of the linear-associator. The goal of this network is to associate a set of stimuli to itself, which could be used to store and retrieve face images and it also could be applied as a pre-processing device to simulate some psychological tasks—such as categorizing face according to their gender. A technique of learning based on the wavelet transform can improve recognition capability when the pattern images are with a great noise. One of the ways to store and recall face images uses the linear auto-associative memory. This connectionist model is in conjunction with a pixel-based coding of the faces. The image processing using t…

Discrete wavelet transformLifting schemePixelComputer sciencebusiness.industrySecond-generation wavelet transformComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONWavelet transformPattern recognitionImage processingFacial recognition systemWaveletComputer visionArtificial intelligencebusiness
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An improved MSD-based method for PD pattern recognition

2007

In this paper a new method for multi source partial discharge (PD) pattern recognition by discrete wavelet transform, is presented. The proposed method is based on the application of multi-resolution signal decomposition (MSD) technique applied to a 3D PD pattern image. The multi-resolution technique has shown that some detail images (horizontal, vertical and diagonal) at different decomposition levels have frequencial characteristics typical of a single discharge phenomenon. By applying this method to a double-source PD pattern it is observed that one source prevails on the other. Taking advantage from the linearity of the biorthogonal wavelet functions by using a removal and reconstructio…

Discrete wavelet transformWaveletLifting schemebusiness.industryComputer scienceStationary wavelet transformSecond-generation wavelet transformPattern recognition (psychology)Pattern recognitionArtificial intelligencebusinessBiorthogonal waveletWavelet packet decomposition2007 Annual Report - Conference on Electrical Insulation and Dielectric Phenomena
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Effect of parametric variation of center frequency and bandwidth of morlet wavelet transform on time-frequency analysis of event-related potentials

2017

Time-frequency (TF) analysis of event-related potentials (ERPs) using Complex Morlet Wavelet Transform has been widely applied in cognitive neuroscience research. It has been widely suggested that the center frequency (fc) and bandwidth (σ) should be considered in defining the mother wavelet. However, the issue how parametric variation of fc and σ of Morlet wavelet transform exerts influence on ERPs time-frequency results has not been extensively discussed in previous research. The current study, through adopting the method of Complex Morlet Continuous Wavelet Transform (CMCWT), aims to investigate whether time-frequency results vary with different parametric settings of fc and σ. Besides, …

Discrete wavelet transformcomplex morlet wavelet transformbandwidthbusiness.industrySpeech recognitionPattern recognitionevent-related potentialsWavelet packet decompositioncenter frequencyWaveletTime–frequency representationMorlet wavelettime-frequency representationArtificial intelligencebusinessContinuous wavelet transformConstant Q transformMathematicsParametric statistics
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EMG artifacts removal during electrical stimulation, a CWT based technique

2014

International audience; A technique of artifacts removal based on the continuous wavelet transform is presented. It uses common mother wavelets to find the temporal localization of stimulation artifacts on electromyogram (EMG) signal during an electrically evoked contraction of a muscle. This method can be used with standard stimulation pulse waveforms like monophasics or biphasics ones. It uses a histogram representation to find the best threshold to apply on the CWT domain. The algotithm is presented with Haar wavelet and then it is used with common wavelet famillies such as Daubechies or Symlets.

Discrete wavelet transformstimulation artifacts0206 medical engineering02 engineering and technologyElectromyography[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing03 medical and health sciences0302 clinical medicineWaveletHistogramwaveletmedicineSource separationWaveformComputer visionContinuous wavelet transformMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing030222 orthopedicsmedicine.diagnostic_testbusiness.industryhistogram representationPattern recognition020601 biomedical engineeringHaar waveletElectromyogram[SPI.TRON]Engineering Sciences [physics]/Electronics[ SPI.TRON ] Engineering Sciences [physics]/Electronicssource separationArtificial intelligencebusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing
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A coupled Finite Volume–Smoothed Particle Hydrodynamics method for incompressible flows

2016

Abstract An hybrid approach is proposed which allows to combine Finite Volume Method (FVM) and Smoothed Particle Hydrodynamics (SPH). The method is based on the partitioning of the computational domain into a portion discretized with a structured grid of hexahedral elements (the FVM-domain ) and a portion filled with Lagrangian particles (the SPH-domain ), separated by an interface made of triangular elements. A smooth transition between the solutions in the FVM and SPH regions is guaranteed by the introduction of a layer of grid cells in the SPH-domain and of a band of virtual particles in the FVM one (both neighboring the interface), on which the hydrodynamic variables are obtained throug…

DiscretizationSPHComputational MechanicsGeneral Physics and AstronomyCoupled FVM–SPH approachBoundary condition01 natural sciences010305 fluids & plasmasSettore ICAR/01 - IdraulicaSmoothed-particle hydrodynamicsPhysics and Astronomy (all)0103 physical sciencesComputational mechanicsMechanics of Material0101 mathematicsMirror particleComputational MechanicPhysicsFinite volume methodMechanical EngineeringMathematical analysisSmoothed Particle HydrodynamicComputer Science Applications1707 Computer Vision and Pattern RecognitionGridComputer Science ApplicationsComputational physics010101 applied mathematicsMechanics of MaterialsCompressibilityReduction (mathematics)Interpolation
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Distributed Learning Automata-based S-learning scheme for classification

2019

This paper proposes a novel classifier based on the theory of Learning Automata (LA), reckoned to as PolyLA. The essence of our scheme is to search for a separator in the feature space by imposing an LA-based random walk in a grid system. To each node in the grid, we attach an LA whose actions are the choices of the edges forming a separator. The walk is self-enclosing, and a new random walk is started whenever the walker returns to the starting node forming a closed classification path yielding a many-edged polygon. In our approach, the different LA attached to the different nodes search for a polygon that best encircles and separates each class. Based on the obtained polygons, we perform …

Distributed learningLearning automataComputer sciencePolygonsFeature vector020207 software engineering02 engineering and technologyGridRandom walkVDP::Matematikk og Naturvitenskap: 400::Informasjons- og kommunikasjonsvitenskap: 420Learning automataSupport vector machinesymbols.namesakeArtificial IntelligenceKernel (statistics)Polygon0202 electrical engineering electronic engineering information engineeringGaussian functionsymbols020201 artificial intelligence & image processingComputer Vision and Pattern RecognitionClassificationsAlgorithmPattern Analysis and Applications
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Pharmacological distribution diagrams: a tool for de novo drug design.

1996

Abstract Discriminant analysis applied to SAR studies using topological descriptors allows us to plot frequency distribution diagrams: a function of the number of drugs within an interval of values of discriminant function vs. these values. We make use of these representations, pharmacological distribution diagrams (PDDs), in structurally heterogeneous groups where generally they adopt skewed Gaussian shapes or present several maxima. The maxima afford intervals of discrimianant function in which exists a good expectancy to find new active drugs. A set of β-blockers with contrasted activity has been selected to test the ability of PDDs as a visualizing technique, for the identification of n…

Distribution (number theory)GaussianAdrenergic beta-AntagonistsBiophysicsInterval (mathematics)Machine learningcomputer.software_genreBiochemistryPlot (graphics)symbols.namesakeDiscriminant function analysisComputer GraphicsPharmacokineticsMathematicsMolecular Structurebusiness.industryDiscriminant AnalysisPattern recognitionFunction (mathematics)Linear discriminant analysisDrug DesignsymbolsArtificial intelligenceMaximabusinesscomputerHalf-LifeJournal of molecular graphics
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Robust stabilisation of 2D state-delayed stochastic systems with randomly occurring uncertainties and nonlinearities

2013

This paper is concerned with the state feedback control problem for a class of two-dimensional (2D) discrete-time stochastic systems with time-delays, randomly occurring uncertainties and nonlinearities. Both the sector-like nonlinearities and the norm-bounded uncertainties enter into the system in random ways, and such randomly occurring uncertainties and nonlinearities obey certain mutually uncorrelated Bernoulli random binary distribution laws. Sufficient computationally tractable linear matrix inequality–based conditions are established for the 2D nonlinear stochastic time-delay systems to be asymptotically stable in the mean-square sense, and then the explicit expression of the desired…

Distribution (number theory)Linear matrix inequality (LMI)Linear matrix inequality2D stochastic systems; Linear matrix inequality (LMI); Randomly occurring nonlinearities; Randomly occurring uncertainties; Control and Systems Engineering; Theoretical Computer Science; Computer Science Applications1707 Computer Vision and Pattern RecognitionBinary numberComputer Science Applications1707 Computer Vision and Pattern RecognitionExpression (computer science)Randomly occurring nonlinearitiesComputer Science ApplicationsTheoretical Computer ScienceNonlinear systemBernoulli's principleControl and Systems EngineeringControl theoryStability theory2D stochastic systemsRandomly occurring uncertaintiesMathematicsInternational Journal of Systems Science
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