Search results for "Estimation"

showing 10 items of 924 documents

Manufactured object sub-segmentation based on reflection motion estimation

2015

International audience; In computer vision, reflection is a long-standing problem, it covers image textures, makes original color difficult to recognize, complicates the understanding of the scene. Most of the time, it is considered as “noise”. Many methods are proposed in order to reduce or delete the reflection effects in the image, but generally, the performances are not quite satisfactory. While instead of working on “de-noising”, we propose a method to take advantage of moving reflections that can be used for different computer vision applications. For instance, the segmentation of reflective manufactured objects is presented in this paper. We focus on tracking reflection components an…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingSegmentation-based object categorizationbusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONScale-space segmentationPattern recognition02 engineering and technologyImage segmentation01 natural sciencesScale space010309 opticsImage texture[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingRegion growingMotion estimation0103 physical sciences0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingComputer visionArtificial intelligenceReflection (computer graphics)businessMathematics
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Noise estimation from digital step-model signal

2013

International audience; This paper addresses the noise estimation in the digital domain and proposes a noise estimator based on the step signal model. It is efficient for any distribution of noise because it does not rely only on the smallest amplitudes in the signal or image. The proposed approach uses polarized/directional derivatives and a nonlinear combination of these derivatives to estimate the noise distribution (e.g., Gaussian, Poisson, speckle, etc.). The moments of this measured distribution can be computed and are also calculated theoretically on the basis of noise distribution models. The 1D performances are detailed, and as our work is mostly dedicated to image processing, a 2D…

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingstep model02 engineering and technology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingCCD sensornoise distributionsymbols.namesake[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processingdigital signalsalt and pepper noiseStatistics0202 electrical engineering electronic engineering information engineeringMedian filterImage noisePoisson noiseValue noiseNoise estimationMathematics[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingedge modelmultiplicative noiseNoise measurementNoise (signal processing)020206 networking & telecommunicationsComputer Graphics and Computer-Aided DesignNoise floorGaussian white noiseGradient noiseimpulse noiseGaussian noisenonlinear modelsymbols020201 artificial intelligence & image processingnoise estimatorAlgorithm[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSoftware
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Recursive estimators 2

1991

In this paper the techniques for recursive estimation of linear model are extended to non-spherical disturbances. First we present the recursive formulae of generalized least squares. The recurrence relation for the residual sum of squares are derived. We show in the second part of the paper a recursive formulae of generalized instrumental variables.

[ MATH ] Mathematics [math]Control theoryStatistics[MATH] Mathematics [math]Estimation récursiveOperational researchRecherche opérationnelleAutomatique
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Analyse et Estimations Spectrales des Processus alpha-Stables non-Stationnaires

2006

In this work a new spectral representation of a symmetric alpha-stable processes is introduced. It is based on a covariation pseudo-additivity and Morse-Transue's integral with respect to a bimesure built by using pseudo-additivity property. This representation, specific to S$\alpha$S processes, is analogous to the covariance of second order processes. On the other hand, it generalizes the representation established for stochastic integrals with respect to symmetric alpha-stable process of independent increments. We provide a classification of non-stationary harmonizable processes; this classification is based on the bimesure structure. In particular, we defined and investigated periodicall…

[ MATH ] Mathematics [math]Densité spectraleSpectral estimation[MATH] Mathematics [math]Estimation spectraleLepage Seriesnon-parametrique StatistiquesPeriodically covariated processesSéries de LepageSpectral AnalysisSpectral densityStrong mixing.Statistiques non paramétriquesMélange fortCovariationProcessus \alpha-stables[MATH]Mathematics [math]Mélange fort.Processus périodiquement covariés\alpha-stable ProcessesAnalyse spectrale
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Spectral density estimation for stationary stable random fields

1995

International audience

[ MATH ] Mathematics [math]Mathematical optimization[ STAT ] Statistics [stat][SPI] Engineering Sciences [physics][MATH] Mathematics [math]01 natural sciences[PHYS] Physics [physics][SPI]Engineering Sciences [physics]010104 statistics & probability[ SPI ] Engineering Sciences [physics]Applied mathematics[MATH]Mathematics [math]0101 mathematicsComputingMilieux_MISCELLANEOUSMathematics[PHYS]Physics [physics][ PHYS ] Physics [physics]Random fieldApplied MathematicsSpectral density estimation[STAT] Statistics [stat][STAT]Statistics [stat]010101 applied mathematicsDiscrete time and continuous timeVariable kernel density estimationKernel embedding of distributionsKernel (statistics)PeriodogramApplicationes Mathematicae
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Naturally constrained reduced form and stuctural parameters estimation

1988

To characterize such a situation, we introduce the concept of a "natural constraint", which is presented and discussed is section 1 of the present paper. Section 2 is concerned with the efficient estimation of the naturally constrained reduced form. From it, we derive efficient estimators of the structural parameters (by indirect GLS) and propose a simple test of the a priori restrictions. In section 3 we discuss estimation by 2SLS. In addition to the resultsobtained by Turkington and Pesaran, we develop a 2SLS-GLS estimator and assess its asymptotic properties. Several full information estimatorsof the 3SLS type are presented and compared in section 4 and some efficiency aspects of the ins…

[ MATH ] Mathematics [math]Regression modelMéthode moindre carréSimultaneous equation systemEstimation statistiqueStatistical estimationDouble moindre carré[MATH] Mathematics [math]Triple moindre carréRegressionModèle régressionSystème équation simultanéeParameter estimationLeast squares methodEstimation paramètre
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Solving chance constrained optimal control problems in aerospace via Kernel Density Estimation

2017

International audience; The goal of this paper is to show how non-parametric statistics can be used to solve some chance constrained optimization and optimal control problems. We use the Kernel Density Estimation method to approximate the probability density function of a random variable with unknown distribution , from a relatively small sample. We then show how this technique can be applied and implemented for a class of problems including the God-dard problem and the trajectory optimization of an Ariane 5-like launcher.

[ MATH.MATH-OC ] Mathematics [math]/Optimization and Control [math.OC]Mathematical optimizationControl and Optimizationchance constrained optimizationKernel density estimation0211 other engineering and technologiesProbability density function02 engineering and technology01 natural sciencesKernel Density Estimation010104 statistics & probability0101 mathematicsMathematics021103 operations researchApplied MathematicsConstrained optimizationTrajectory optimizationstochastic optimizationOptimal controlOptimal controlDistribution (mathematics)Aerospace engineeringControl and Systems EngineeringStochastic optimization[MATH.MATH-OC]Mathematics [math]/Optimization and Control [math.OC]Random variableSoftware
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Functional ecology for evaluating and predicting the aptitude of permanent grassland to provide services

2013

National audience; Applying the principles of functional ecology helps better predict the services which can be provided by permanent grassland. Farming practices and environmental characteristics influence the functional composition of grassland. Functional plant types have a generic effect on forage services which can be assessed. 13 types of grassland composed of distinct functional types were defined based on 1,283 sample grassland fields located on 8 sites. This approach was validated by checking 8 Ellenberg indicator values (used to evaluate environmental characteristics and farming practices) against climatic data and descriptive data for farming practices. The interest of a function…

[ SDV ] Life Sciences [q-bio]flexibility of managementgrasspasture management practices[SDV]Life Sciences [q-bio]forage productionseasonal variationsBiodiversitygrassland typologynutritive valuenitrogenfertilisation[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio]functional compositionenvironmental factorvegetation[SDE]Environmental Sciencesforage system[SDV.BV]Life Sciences [q-bio]/Vegetal Biologyutilization value of grasslandsservices provided by grasslandpermanent pastureestimation method
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Computerized delimitation of odorant areas in gas-chromatography-olfactometry by kernel density estimation: Data processing on French white wines

2017

International audience; GC-O using the detection frequency method gives a list of odor events (OEs) where each OE is described by a linear retention index (LRI) and by the aromatic descriptor given by a human assessor. The aim of the experimenter is to gather OEs in a total olfactogram on which he tries to delimit odorant areas (OAs), then to compute each detection frequency. This paper proposes a computerized mathematical method based on kernel density estimation that makes up the total olfactogram as continuous and differentiable function from the OEs LRI only. The corresponding curve looks like a chromatogram, the peaks of which are potential OAs. The limits of an OA are the LRI of the t…

[ SDV.AEN ] Life Sciences [q-bio]/Food and NutritionKernel density estimation01 natural sciencesolfactogramAnalytical ChemistrySet (abstract data type)0404 agricultural biotechnologyStatisticsRange (statistics)Kernel densitu estimationSpectroscopyMathematicsContingency tableProcess Chemistry and Technology010401 analytical chemistry04 agricultural and veterinary sciencesdetection frequency method040401 food science0104 chemical sciencesComputer Science ApplicationsMaxima and minimaGC olphactometryKernel (statistics)Benchmark (computing)Kovats retention indexParzen-Rosenblatt[SDV.AEN]Life Sciences [q-bio]/Food and NutritionSoftware
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Extrapolation des inventaires de biodiversité incomplets : comment estimer au mieux le nombre d’espèces manquantes et prévoir l’effort additionnel d’…

2016

While approaching or even reaching total completeness remains the idealgoal of any species inventory, incomplete samplings are deemed to become more often the rule, that are significantly more difficult to cope with (such as (micro-) invertebrates, for example).However, once post-operated appropriately, incomplete samplings may provide farmore data than it would seem and it is indeed possible to obtain valuable extra information froma reliable mode of extrapolation of the so-called Species Accumulation Curve.In fact, numerous tools designed for the exploitation of incomplete samplings havealready been proposed in the literature but the concern, with these numerous different tools, isprecise…

[ SDV.BID ] Life Sciences [q-bio]/Biodiversityrichesse spécifiqueéchantillonnage incompletestimationextrapolationInventaireChaoestimatorcompletenessSpecies Accumulation CurveCourbe d’Accumulation des EspècesJackknifeincomplete samplingspecies richnessSurvey[SDV.BID] Life Sciences [q-bio]/Biodiversity
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