Search results for "pattern"

showing 10 items of 4203 documents

A Support Vector Domain Description Approach to Supervised Classification of Remote Sensing Images

2007

This paper addresses the problem of supervised classification of remote sensing images in the presence of incomplete (nonexhaustive) training sets. The problem is analyzed according to two different perspectives: 1) description and recognition of a specific land-cover class by using single-class classifiers and 2) solution of multiclass problems with single-class classification techniques. In this framework, we analyze different one-class classifiers and introduce in the remote sensing community the support vector domain description method (SVDD). The SVDD is a kernel-based method that exhibits intrinsic regularization ability and robustness versus low numbers of high-dimensional samples. T…

Contextual image classificationbusiness.industryHyperspectral imagingPattern recognitionMachine learningcomputer.software_genreMulticlass classificationSupport vector machineStatistical classificationKernel methodRobustness (computer science)ScalabilityGeneral Earth and Planetary SciencesArtificial intelligenceElectrical and Electronic EngineeringbusinesscomputerRemote sensingMathematicsIEEE Transactions on Geoscience and Remote Sensing
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Graph matching for efficient classifiers adaptation

2011

In this work we present an adaptation algorithm focused on the description of the measurement changes under different acquisition conditions. The adaptation is carried out by transforming the manifold in the first observation conditions into the corresponding manifold in the second. The eventually non-linear transform is based on vector quantization and graph matching. The transfer learning mapping is defined in an unsupervised manner. Once this mapping has been defined, the labeled samples in the first are projected into the second domain, thus allowing the application of any classifier in the transformed domain. Experiments on VHR series of images show the validity of the proposed method …

Contextual image classificationbusiness.industryImage matchingVector quantizationVector quantisationPattern recognitionManifoldSupport vector machineLife ScienceArtificial intelligenceTransfer of learningbusinessClassifier (UML)Mathematics
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Encoding Invariances in Remote Sensing Image Classification With SVM

2013

This letter introduces a simple method for including invariances in support-vector-machine (SVM) remote sensing image classification. We design explicit invariant SVMs to deal with the particular characteristics of remote sensing images. The problem of including data invariances can be viewed as a problem of encoding prior knowledge, which translates into incorporating informative support vectors (SVs) that better describe the classification problem. The proposed method essentially generates new (synthetic) SVs from the obtained by training a standard SVM with the available labeled samples. Then, original and transformed SVs are used for training the virtual SVM introduced in this letter. W…

Contextual image classificationbusiness.industryPattern recognitionInvariant (physics)Geotechnical Engineering and Engineering GeologySupport vector machineComputingMethodologies_PATTERNRECOGNITIONRobustness (computer science)Computer visionArtificial intelligenceElectrical and Electronic EngineeringbusinessMathematicsRemote sensingIEEE Geoscience and Remote Sensing Letters
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Incorporating in vivo and ex vivo NMR sources of information for modeling robust brain tumor classifiers

2010

The purpose of this paper is to investigate the potential and limitations of using multimodal sources of information coming from in vivo NMR and ex vivo NMR data for detecting brain tumors. Supervised pattern recognition methods, whose performance directly depends on the prior available observations used in building them, are proposed. We show that high resolution magic angle spinning (HR-MAS) data act as complementary information for classifying magnetic resonance spectroscopic imaging (MRSI) data. In particularly, when considering rare brain tumors, since it is unlikely to acquire sufficient cases to define their metabolite profiles using only in vivo NMR information, HR-MAS can support t…

Contextual image classificationmedicine.diagnostic_testComputer sciencebusiness.industryMagnetic resonance spectroscopic imagingPattern recognitionMagnetic resonance imagingData modelingNuclear magnetic resonanceIn vivoPattern recognition (psychology)Magic angle spinningmedicineArtificial intelligencebusinessEx vivo2010 IEEE International Conference on Imaging Systems and Techniques
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A non-supervised approach to locate and to measure the nuchal translucency by means of wavelet analysis and neural networks

2017

Ultrasound imaging is a well known noninvasive way to evaluate various diseases during the prenatal age. In particular, the thickness measure of the nuchal transucency is strictly correlated with pathologies like trisomy 13, 18 and 21. For a correct investigation, the methodology needs mid-sagittal sections and the proposed approach is based on wavelet analysis and neural network classifiers to locate components useful to identify mid-sagittal planes. To evaluate the performance and the robustness of the methodology, real clinical ultrasound images were considered, obtaining an average error of at most 0.3 millimeters in 97.4% of the cases.

Control and OptimizationArtificial neural networkSettore INF/01 - InformaticaComputer sciencebusiness.industrymid-sagittal sectionneural networksymmetry transformPattern recognitionMeasure (mathematics)Ultrasonic imagingClinical ultrasoundWaveletComputer Networks and CommunicationNuchal translucencyRobustness (computer science)Artificial IntelligenceUltrasound imagingArtificial intelligencewavelet analysibusinessnuchal translucencyInformation Systems
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Reliable Planar Object Pose Estimation in Light Fields From Best Subaperture Camera Pairs

2018

International audience; A light-field camera can obtain richer information about a scene than a usual camera. This property offers a lot of potential for robot vision. In this paper, we present a method for pose estimation of a planar object with a light-field camera. The light-field camera can be regarded as a set of sub-aperture cameras. Although any combination of them can theoretically be used for the pose estimation, the accuracy depends on the combination. We show that the estimated pose error can be reduced by selecting the best pair of sub-aperture cameras. We have evaluated the accuracy of our approach with real experiments using a light-field camera in front of planar targets held…

Control and OptimizationComputer scienceProperty (programming)Biomedical EngineeringComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSet (abstract data type)PlanarArtificial Intelligence[INFO.INFO-RB]Computer Science [cs]/Robotics [cs.RO]Computer visionPoseComputer Science::DatabasesGround truthbusiness.industryMechanical EngineeringAstrophysics::Instrumentation and Methods for Astrophysics[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]16. Peace & justiceObject (computer science)Computer Science ApplicationsHuman-Computer InteractionControl and Systems EngineeringComputer Science::Computer Vision and Pattern RecognitionComputer Vision and Pattern RecognitionArtificial intelligencebusiness
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A Short-Term Data Based Water Consumption Prediction Approach

2019

A smart water network consists of a large number of devices that measure a wide range of parameters present in distribution networks in an automatic and continuous way. Among these data, you can find the flow, pressure, or totalizer measurements that, when processed with appropriate algorithms, allow for leakage detection at an early stage. These algorithms are mainly based on water demand forecasting. Different approaches for the prediction of water demand are available in the literature. Although they present successful results at different levels, they have two main drawbacks: the inclusion of several seasonalities is quite cumbersome, and the fitting horizons are not very large. With th…

Control and OptimizationSimilarity (geometry)010504 meteorology & atmospheric sciencesComputer science0208 environmental biotechnologywaterEnergy Engineering and Power TechnologyContext (language use)forecasting02 engineering and technologycomputer.software_genre01 natural scienceslcsh:TechnologyWater consumptionpattern-basedPattern-basedRange (statistics)medicineSDG 7 - Affordable and Clean EnergyElectrical and Electronic EngineeringLeakage (economics)Machine-learningEngineering (miscellaneous)0105 earth and related environmental sciencesMeasure (data warehouse)Renewable Energy Sustainability and the Environmentlcsh:Tmachine-learningWaterSeasonalityDemand forecastingmedicine.disease020801 environmental engineeringWater demandTerm (time)Stage (hydrology)Data miningcomputerForecastingEnergy (miscellaneous)Energies
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Multi-Dimensional Pattern Matching with Dimensional Wildcards: Data Structures and Optimal On-Line Search Algorithms

1997

We introduce a new multidimensional pattern matching problem that is a natural generalization of string matching, a well studied problem1. The motivation for its algorithmic study is mainly theoretical. LetA1:n1,?,1:nd be a text matrix withN=n1?ndentries andB1:m1,?,1:mr be a pattern matrix withM=m1?mrentries, whered?r?1 (the matrix entries are taken from an ordered alphabet ?). We study the problem of checking whether somer-dimensional submatrix ofAis equal toB(i.e., adecisionquery).Acan be preprocessed andBis given on-line. We define a new data structure for preprocessingAand propose CRCW-PRAM algorithms that build it inO(logN) time withN2/nmaxprocessors, wherenmax=max(n1,?,nd), such that …

Control and OptimizationSuffix treeBlock matrixWildcard characterString searching algorithmcomputer.file_formatData structurelaw.inventionCombinatoricsComputational MathematicsMatrix (mathematics)Computational Theory and MathematicsSearch algorithmlawPattern matchingcomputerMathematicsJournal of Algorithms
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Heat and mass transfer phenomena in magnetic fluids

2007

In this article the influence of a magnetic field on heat and mass transport phenomena in magnetic fluids (ferrofluids) will be discussed. The first section is dealing with a magnetically driven convection, the so called thermomagnetic convection while in the second section the influence of a temperature gradient on the mass transport, the Soret effect in ferrofluids, is reviewed. (© 2007 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)

ConvectionMass transportFerrofluidMaterials scienceCondensed matter physicsApplied MathematicsGeneral Physics and AstronomyThermomagnetic convectionThermophoresisMagnetic fieldPhysics::Fluid DynamicsTemperature gradientMass transferGeneral Materials ScienceNonlinear Sciences::Pattern Formation and SolitonsGAMM-Mitteilungen
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Magnetic field driven micro-convection in the Hele-Shaw cell

2013

AbstractMicro-convection caused by ponderomotive forces of the self-magnetic field of a magnetic fluid in the Hele-Shaw cell under the action of a vertical homogeneous magnetic field is studied both experimentally and numerically. It is shown that a non-potential magnetic force at magnetic Rayleigh numbers greater than the critical value causes fingering at the interface between the miscible magnetic and non-magnetic fluids. The threshold value of the magnetic Rayleigh number depends on the smearing of the interface between fluids. Fingering with its subsequent decay due to diffusion of particles significantly increases the mixing at the interface. Velocity and vorticity fields at fingering…

ConvectionPhysicsField (physics)Mechanical EngineeringMechanicsRayleigh numberVorticityequipment and suppliesCondensed Matter PhysicsCritical valueMagnetic fieldPhysics::Fluid DynamicsHele-Shaw flowParticle image velocimetryMechanics of Materialshuman activitiesNonlinear Sciences::Pattern Formation and SolitonsJournal of Fluid Mechanics
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