Search results for "Détection"

showing 10 items of 77 documents

The 2009 Edition of the GEISA Spectroscopic Database

2011

The updated 2009 edition of the spectroscopic database GEISA (Gestion et Etude des Informations Spectroscopiques Atmosphériques; Management and Study of Atmospheric Spectroscopic Information) is described in this paper. GEISA is a computer-accessible system comprising three independent sub-databases devoted, respectively, to: line parameters, infrared and ultraviolet/visible absorption cross-sections, microphysical and optical properties of atmospheric aerosols. In this edition, 50 molecules are involved in the line parameters sub-database, including 111 isotopologues, for a total of 3,807,997 entries, in the spectral range from 10-6 to 35,877.031cm-1.The successful performances of the new …

010504 meteorology & atmospheric sciencesMeteorologyTélédétectionPhysique atomique et moléculaireMolecular spectroscopyInfrared atmospheric sounding interferometercomputer.software_genre01 natural sciencesLine parametersAtmospheric radiative transfer0103 physical sciences010303 astronomy & astrophysicsSpectroscopy0105 earth and related environmental sciencesRemote sensingWeb site[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]RadiationSpectroscopic database[ PHYS.PHYS.PHYS-OPTICS ] Physics [physics]/Physics [physics]/Optics [physics.optics]DatabaseGEISAOptically activeAtmospheric aerosolsMolecular spectroscopyAtomic and Molecular Physics and Optics[CHIM.THEO]Chemical Sciences/Theoretical and/or physical chemistryOn boardSpectroscopie [électromagnétisme optique acoustique][ CHIM.THEO ] Chemical Sciences/Theoretical and/or physical chemistryEarth's and planetary atmospheresEnvironmental scienceAtmospheric absorptionAtmospheric absorptionCross-sectionscomputer
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A multisensor fusion approach to improve LAI time series

2011

International audience; High-quality and gap-free satellite time series are required for reliable terrestrial monitoring. Moderate resolution sensors provide continuous observations at global scale for monitoring spatial and temporal variations of land surface characteristics. However, the full potential of remote sensing systems is often hampered by poor quality or missing data caused by clouds, aerosols, snow cover, algorithms and instrumentation problems. A multisensor fusion approach is here proposed to improve the spatio-temporal continuity, consistency and accuracy of current satellite products. It is based on the use of neural networks, gap filling and temporal smoothing techniques. …

010504 meteorology & atmospheric sciencesMeteorologytélédétectionsatellite0211 other engineering and technologiesSoil Scienceréseau neuronal02 engineering and technology01 natural sciencessuivi de culturesInstrumentation (computer programming)Computers in Earth SciencesLeaf area index021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingVegetationGeologyVegetationData fusionLAI time seriesSensor fusionMissing dataLAI time series;Vegetation;Modis;Temporal smoothing;Gap filling;Data fusionqualité des données13. Climate actionAutre (Sciences de l'ingénieur)Gap filling[SDE]Environmental SciencesEnvironmental scienceSatelliteModisTemporal smoothingScale (map)Smoothing
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Modelling soil moisture at SMOS scale by use of a SVAT model over the Valencia Anchor Station

2010

16 páginas, 9 figuras, 5 tablas.

010504 meteorology & atmospheric sciencestélédétectionMISSION SMOS0211 other engineering and technologiesSpaceespagne02 engineering and technologylcsh:Technology01 natural sciencesValidationTraitement du signal et de l'imagelcsh:Environmental technology. Sanitary engineering020701 environmental engineeringWater contentlcsh:Environmental sciencesComputingMilieux_MISCELLANEOUSlcsh:GE1-350InclusionRetrievalMoistureModelling soil moistureSignal and Image processinglcsh:Geography. Anthropology. RecreationRemote sensingDISPOSITIF EXPERIMENTAL; MISSION SMOSProductseurope[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingSMOS[SDE.MCG]Environmental Sciences/Global Changessatellite0207 environmental engineeringGrowing seasonParameterizationSpatial distributionlcsh:TD1-1066SchemeHapexspectroradiomètre14. Life underwater[SDU.STU.HY]Sciences of the Universe [physics]/Earth Sciences/Hydrology021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometerlcsh:TAMSR-Epays méditerranéenSalinityERS scatterometerlcsh:G13. Climate actionDISPOSITIF EXPERIMENTALSoil waterEnvironmental scienceRadiometry
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Global-Scale Evaluation of Roughness Effects on C-Band AMSR-E Observations

2015

Quantifying roughness effects on ground surface emissivity is an important step in obtaining high-quality soil moisture products from large-scale passive microwave sensors. In this study, we used a semi-empirical method to evaluate roughness effects (parameterized here by the parameter) on a global scale from AMSR-E (Advanced Microwave Scanning Radiometer for EOS) observations. AMSR-E brightness temperatures at 6.9 GHz obtained from January 2009 to September 2011, together with estimations of soil moisture from the SMOS (Soil Moisture and Ocean Salinity) L3 products and of soil temperature from ECMWF’s (European Centre for Medium-range Weather Forecasting) were used as inputs in a retrieval…

010504 meteorology & atmospheric sciencestélédétectionScience0211 other engineering and technologiesWeather forecasting[SDU.STU]Sciences of the Universe [physics]/Earth SciencesElectromagnétismesoil surface roughness02 engineering and technologySurface finishcomputer.software_genredonnée satellite01 natural sciencesSciences de la TerreNormalized Difference Vegetation Indexsoil moisture;soil surface roughness;AMSR-EElectromagnetismEmissivitySurface roughnessTraitement du signal et de l'image14. Life underwaterWater content021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingRadiometercapteur smosQSignal and Image processingradiométrie microondesVegetationAMSR-E15. Life on land[SPI.ELEC]Engineering Sciences [physics]/ElectromagnetismEarth SciencesGeneral Earth and Planetary SciencesEnvironmental sciencesoil moisturecomputer[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingRemote Sensing
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Vegetation structure and greenness in Central Africa from Modis multi-temporal data.

2013

African forests within the Congo Basin are generally mapped at regional scale as broad-leaved evergreen forests, with a main distinction between terra-firme and swamp forests types. At the same time, commercial forest inventories, as well as national maps, have highlighted a strong spatial heterogeneity of forest types. A detailed vegetation map generated using consistent methods is needed to inform decision makers about spatial forest organisation and theirs relationships with environmental drivers in the context of global change. We propose a multi-temporal remotely sensed data approach to characterize vegetation types using vegetation index annual profiles. The classifications identified…

0106 biological scienceshttp://aims.fao.org/aos/agrovoc/c_28568Time Factors010504 meteorology & atmospheric sciencesDatabases FactualRainEcological Parameter Monitoringhttp://aims.fao.org/aos/agrovoc/c_900018001 natural sciencesTrees[ SDE ] Environmental Sciencesremote sensinghttp://aims.fao.org/aos/agrovoc/c_3062K01 - Foresterie - Considérations généralesDynamique des populationsForêt tropicale humidehttp://aims.fao.org/aos/agrovoc/c_6498http://aims.fao.org/aos/agrovoc/c_29008geography.geographical_feature_categoryCentral AfricaEcologyInventaire forestierVegetationArticlesClassificationSpatial heterogeneity[ SDE.MCG ] Environmental Sciences/Global ChangesDeciduoushttp://aims.fao.org/aos/agrovoc/c_7976CongoP31 - Levés et cartographie des solsForêt[SDE]Environmental SciencesSeasonshttp://aims.fao.org/aos/agrovoc/c_1432General Agricultural and Biological Scienceshttp://aims.fao.org/aos/agrovoc/c_34911Research ArticleF40 - Écologie végétaleTélédétectionClimate Change[SDE.MCG]Environmental Sciences/Global ChangesSpectroscopie infrarougeContext (language use)69Typologie010603 evolutionary biologySwampGeneral Biochemistry Genetics and Molecular BiologyCarbon Cycle[ SDU.ENVI ] Sciences of the Universe [physics]/Continental interfaces environmentHumansAfrica Centralhttp://aims.fao.org/aos/agrovoc/c_1666http://aims.fao.org/aos/agrovoc/c_1344http://aims.fao.org/aos/agrovoc/c_8176[SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces environmenthttp://aims.fao.org/aos/agrovoc/c_6111Ecosystem0105 earth and related environmental sciencesChangement climatiquegeographyCartographiehttp://aims.fao.org/aos/agrovoc/c_24174Enhanced vegetation index15. Life on landEvergreenVégétationStructure du peuplement13. Climate actionCouvert forestierPhysical geographyU30 - Méthodes de recherchehttp://aims.fao.org/aos/agrovoc/c_1653tropical rainforestTropical rainforest
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Risque phytosanitaire (ARP) portant sur Fusarium oxysporum f. sp. cubense (agent pathogène responsable de la maladie de Panama) pour les départements…

2018

Risque phytosanitaire (ARP) portant sur [i]Fusarium oxysporum[/i] f. sp.[u] cubense[/u] (agent pathogène responsable de la maladie de Panama) pour les départements d'Outre-mer

Analyse de risque phytosanitaire[SDV.SA]Life Sciences [q-bio]/Agricultural sciences[SDV.SA] Life Sciences [q-bio]/Agricultural sciencesoutre mer françaisétat de l'artrisque économiqueregulationweed control methodsrace tropicale 4champignon phytopathogèneexpertise scientifiquephytopathogenic fungusbananedétection[SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyFoc TR4méthode de luttemaladie de PanamaFusarium oxysporum f. sp. cubenseréglementationpathologie végétale[SDV.BV.PEP] Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacyéconomie des filières
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Real-time 3D movements analysis for a medical device intended for maintaining functional independence in aged adults at home

2016

We propose in this manuscript a realtime3D movement analysis system for inhomefunctionalabilities assessment in aged adults. As a first step, the purpose is to maintain the functionalindependence of this population and to allow an earlier detection of a motor decompensation inorder to facilitate a rehabilitation process. To quantify the equilibrium quality of a subject, webuilt a system using the Kinect sensor in order to analyze a simple clinical test validated in geriatricrehabilitation: the Timed Up and Go (TUG). Three experiments conducted in heterogeneousenvironments (laboratory, day hospital and home) showed good measurement reliability of theidentified parameters. In particular, they…

Analyse des mouvements 3D en temps réelElderly persons[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Evaluation automatique des capacités fonctionnellesNote de contrôle moteur[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Segmentation des personnesExtraction des paramètres spatiotemporelsTimed Up and GoPersonnes âgéesFragilité motriceDétection de la région de peauDétection de la position assise
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Computer-aided-diagnosis for ocular abnormalities from a single color fundus photography with deep learning

2023

Any damage to the retina can lead to severe consequences like blindness. This visual impairment is preventable by early detection of ocular abnormalities. Computer-aided diagnosis (CAD) for ocular abnormalities is built by analyzing retinal imaging modalities, for instance, Color Fundus Photography (CFP). The main objectives of this thesis are to build two CAD models, one to detect the microaneurysms (MAs), the first visible symptom of diabetic retinopathy, and the other for multi-label detection of 28 ocular abnormalities consisting of frequent and rare abnormalities from a single CFP by using deep learning-based approaches. Two methods were proposed for MAs detection: ensemble-based and c…

Apprentissage profondTraitement des imagesAnomalies oculairesImage processingMicroaneurysms detectionOcular abnormalities[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingDétection de microanévrismesDeep learningMulti-Label detectionComputer-Aided-DiagnosisDiagnostic automatiqueDétection multi-Étiquettes
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PCR La confluence Saône-Doubs à l'âge du Fer (Vie s. av. J.-C. au Ier siècle de notre ère): Annexes. Vol. 2

2020

https://www.nakala.fr/data/11280/8d5ff3f9; Ce rapport est un document administratif destiné à rendre compte des actions réalisées au cours de l’année 2019 dans le cadre du Projet Collectif de Recherche consacré à la confluence Saône-Doubs à l’âge du Fer, coordonné par Emilie Dubreucq et Matthieu Thivet

Archélogie[SHS.ARCHEO] Humanities and Social Sciences/Archaeology and PrehistoryArchéométrie[SHS.ARCHEO]Humanities and Social Sciences/Archaeology and PrehistoryTélédétectionBioarcheologieCulture MatérielleGéophysiquesPaléoenvironnementsAnalyse documentaire
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Conception d'architectures compactes pour la détection spatiotemporelle d'actions en temps réel

2022

This thesis tackles the spatiotemporal action detection problem from an online, efficient, and real-time processing point of view. In the last decade, the explosive growth of video content has driven a broad range of application demands for automating human action understanding. Aside from accurate detection, vast sensing scenarios in the real-world also mandate incremental, instantaneous processing of scenes under restricted computational budgets. However, current research and related detection frameworks are incapable of simultaneously fulfilling the above criteria. The main challenge lies in their heavy architectural designs and detection pipelines to extract pertinent spatial and tempor…

Artificial intelligenceApprentissage profond[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingDeep learningDétection d'actionsIntelligence artificielleAction detection
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