Search results for "Spatial"

showing 10 items of 2121 documents

Learning spatial filters for multispectral image segmentation.

2010

International audience; We present a novel filtering method for multispectral satel- lite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments car- ried out on multiclass one-against-all classification and tar- get detection show the capabilities of the learned spatial fil- ters.

Computer Science::Machine LearningMultispectral image0211 other engineering and technologies02 engineering and technology01 natural sciencesRegularization (mathematics)010104 statistics & probability[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG]Life ScienceComputer visionSegmentation0101 mathematicsLarge margin method021101 geological & geomatics engineeringMathematicsImage segmentationContextual image classificationPixelbusiness.industryPattern recognitionImage segmentationSupport vector machineComputingMethodologies_PATTERNRECOGNITIONmultispectral imageSpatial FilteringArtificial intelligenceGradient descentbusiness
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The community structure of the global corporate network.

2013

We investigate the community structure of the global ownership network of transnational corporations. We find a pronounced organization in communities that cannot be explained by randomness. Despite the global character of this network, communities reflect first of all the geographical location of firms, while the industrial sector plays only a marginal role. We also analyze the network in which the nodes are the communities and the links are obtained by aggregating the links among firms belonging to pairs of communities. We analyze the network centrality of the top 50 communities and we provide the first quantitative assessment of the financial sector role in connecting the global economy.

Computer and Information SciencesPhysics - Physics and SocietyEconomicsEconomic ModelsPopulation DynamicsSocial SciencesSpatial Economic Analysislcsh:MedicineFOS: Physical sciencesGenetics and Molecular Biology1100 General Agricultural and Biological SciencesPhysics and Society (physics.soc-ph)Economic GeographySystems ScienceFOS: Economics and businessDevelopment Economics1300 General Biochemistry Genetics and Molecular BiologyHumansIndustrylcsh:ScienceStructure of Markets1000 MultidisciplinaryGeographyApplied MathematicsPhysicslcsh:RInternational AgenciesIndustrial OrganizationComplex SystemsGeneral MedicineOrganizational Culture10003 Department of Banking and FinanceEconomic Analysis330 EconomicsMathematical EconomicsGeneral BiochemistryPhysical SciencesEarth SciencesInterdisciplinary Physicslcsh:QEconomic DevelopmentGeneral Agricultural and Biological SciencesQuantitative Finance - General FinanceGeneral Finance (q-fin.GN)MathematicsResearch ArticlePloS one
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Enhanced Mathematical Modelling of Interior Permanent Magnet Synchronous Machine Considering Saturation, Cross-Coupling and Spatial Harmonics effects

2020

The Interior Permanent Magnet Synchronous machine (IPMSM) conventional mathematical model is generally employed to investigate and simulate the IPMSM control and drive system behaviour. However, magnetic nonlinearities and spatial harmonics have a substantial influence on the IPMSM electromagnetic behaviour and performances. In order to simulate the IPMSM real electromagnetic behaviour, this paper describes an enhanced mathematical model that takes into account the saturation, cross-coupling and spatial harmonics effects. This model has been implemented in Matlab®/Simulink environment where the electric and magnetic parameters are derived from FEA investigations and implemented by the use o…

Computer science020208 electrical & electronic engineering05 social sciences02 engineering and technologySettore ING-IND/32 - Convertitori Macchine E Azionamenti ElettriciFinite element methodSpatial harmonicsCross-coupling Finite Element Analysis (FEA) Interior Permanent Magnet Synchronous Machine (IPMSM) saturation spatial harmonicsHigh fidelityControl theoryLookup table0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesSaturation (magnetic)Permanent magnet synchronous machine050107 human factors2020 Fifteenth International Conference on Ecological Vehicles and Renewable Energies (EVER)
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A comparison of STARFM and an unmixing-based algorithm for Landsat and MODIS data fusion

2015

article i nfo The focus of the current study is to compare data fusion methods applied to sensors with medium- and high- spatial resolutions. Two documented methods are applied, the spatial and temporal adaptive reflectance fusion model (STARFM) and an unmixing-based method which proposes a Bayesian formulation to incorporate prior spectral information.Furthermore, thestrengths of both algorithms arecombined ina novel data fusionmethod: the Spatial and Temporal Reflectance Unmixing Model (STRUM). The potential of each method is demonstrated using simulation imagery and Landsat and MODIS imagery. The theoretical basis of the algorithms causes STARFM and STRUM to produce Landsat-like reflecta…

Computer scienceBayesian formulationSpatial ecologySoil ScienceGeologyMETIS-308148Computers in Earth SciencesSensor fusionFocus (optics)ReflectivityAlgorithmNormalized Difference Vegetation IndexRemote sensingRemote Sensing of Environment
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A new Adaptive and Progressive Image Transmission Approach using Function Superpositions

2010

International audience; We present a novel approach to adaptive and progressive image transmission, based on the decomposition of an image into compositions and superpositions of monovariate functions. The monovariate functions are iteratively constructed and transmitted, one after the other, to progressively reconstruct the original image: the progressive transmission is performed directly in the 1D space of the monovariate functions and independently of any statistical properties of the image. Each monovariate function contains only a fraction of the pixels of the image. Each new transmitted monovariate function adds data to the previously transmitted monovariate functions. After each tra…

Computer scienceImage qualityComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyIterative reconstructionmultidimensional function decompositionSuperposition principleRobustness (computer science)[ INFO.INFO-TI ] Computer Science [cs]/Image Processing0202 electrical engineering electronic engineering information engineeringComputer visionsignal processingspatial scalability.Image resolutionImage restorationSignal processingPixelbusiness.industryprogressive image transmissionGeneral Engineering020206 networking & telecommunicationsAtomic and Molecular Physics and Opticsfunctional representation[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Computer Science::Computer Vision and Pattern RecognitionKolmogorov superposition theorem020201 artificial intelligence & image processingTomographyArtificial intelligencebusinessDigital filterAlgorithmspatial scalabilityImage compression
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Identification of differential risk hotspots for collision and vehicle type in a directed linear network

2019

Traffic accidents can take place in very different ways and involve a substantially distinct number and types of vehicles. Thus, it is of interest to know which parts of a road structure present an overrepresentation of a specific type of traffic accident, specially for some typologies of collisions and vehicles that tend to trigger more severe consequences for the users being involved. In this study, a spatial approach is followed to estimate the risk that different types of collisions and vehicles present in the central area of Valencia (Spain), considering the accidents observed in this city during the period 2014-2017. A directed spatial linear network representing the non-pedestrian ro…

Computer scienceKernel density estimationPoison controlHuman Factors and Ergonomicscomputer.software_genreRisk Assessment0502 economics and businessHumans0501 psychology and cognitive sciencesBuilt EnvironmentSafety Risk Reliability and QualitySpatial analysis050107 human factorsSpatial Analysis050210 logistics & transportation05 social sciencesAccidents TrafficPublic Health Environmental and Occupational HealthDifferential (mechanical device)CollisionMotor VehiclesIdentification (information)SpainSample size determinationData miningRisk assessmentMonte Carlo MethodcomputerAccident Analysis & Prevention
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A Comparison of Advanced Regression Algorithms for Quantifying Urban Land Cover

2014

Quantitative methods for mapping sub-pixel land cover fractions are gaining increasing attention, particularly with regard to upcoming hyperspectral satellite missions. We evaluated five advanced regression algorithms combined with synthetically mixed training data for quantifying urban land cover from HyMap data at 3.6 and 9 m spatial resolution. Methods included support vector regression (SVR), kernel ridge regression (KRR), artificial neural networks (NN), random forest regression (RFR) and partial least squares regression (PLSR). Our experiments demonstrate that both kernel methods SVR and KRR yield high accuracies for mapping complex urban surface types, i.e., rooftops, pavements, gras…

Computer scienceLand coverimaging spectrometrysub-pixel mappingKernel (linear algebra)urban land coverPartial least squares regressionlcsh:Sciencespatial resolutionHyMapRemote sensingmachine learning; regression; sub-pixel mapping; spatial resolution; imaging spectrometry; hyperspectral; urban land coverTraining setArtificial neural networkbusiness.industryHyperspectral imagingPattern recognitionRandom forestSupport vector machineKernel methodmachine learninghyperspectralKernel (statistics)General Earth and Planetary Sciencesregressionlcsh:QArtificial intelligencebusinessRemote Sensing
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Does force-field adaptation induce after-effects on space representation?

2017

AbstractPrism adaptation is a well-known model to study sensorimotor adaptive processes. It has been shown that following prism exposure, after-effects are not only restricted to the sensorimotor level but extend as well into spatial cognition. The main purpose of the present study was to investigate in healthy individuals whether expansion to spatial cognition is restricted to adaptive processes peculiar to prism adaptation or whether it occurs as well following other forms of adaptive process such as adaptation to a novel dynamic environment during pointing movements. Representational after-effects were assessed by the perceptual line bisection task before and after adaptation to a leftwa…

Computer scienceLate phaseBisectionHealthy individualsPerceptionmedia_common.quotation_subjectSpatial cognitionPrism adaptationForce field (chemistry)media_commonCognitive psychology
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Are simple striate cells analysers of visual signals both in spatial position as well as in spatial frequency?

1984

According to a modern view, simple cells of the cat striate cortex are considered to operate as apart of Fourier analysis system thus leading to the idea that the operational mechanism of the visual cortex is concerned with the analysis of spatial frequencies. Nevertheless if simple cells are really concerned only with the analysis of spatial frequencies there should exist a strict relationship between their spatial frequency selectivity and the spatial organization of their receptive fields. This is because it is the spatial organization of the spatial frequency detector i.e. the cell's receptive field that determines the cell's spatial frequency selectivity. Since the quantitative analysi…

Computer scienceMotion PerceptionDermatologySimple cellsymbols.namesakePsychophysicsmedicineAnimalsBinocular neuronsSpatial organizationVisual CortexFourier AnalysisGeneral NeuroscienceNeural AnalyzersDetectorGeneral MedicinePsychiatry and Mental healthVisual cortexmedicine.anatomical_structureFourier analysisReceptive fieldSpace PerceptionCatssymbolsNeurology (clinical)Spatial frequencyVisual FieldsBiological systemNeuroscienceThe Italian Journal of Neurological Sciences
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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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