Search results for " Computer science"

showing 10 items of 3983 documents

3D ACQUISITION SYSTEM APPLIED TO AGRONOMIC SCENES

2012

International audience; To improve results in automatic wheat ear counting by proxy-detection for early yield prediction, we need depth information of the scene. In this paper, we describe our 3D acquisition system dedicated to reconstruction of agronomic scenes. This system is composed of a camera mounted on a linear displacement driven by a microcontroller. The linear displacement allows acquiring a set of images in different distances to the scene. This image stack is used to apply shape from focus technique which is a passive and monocular 3D reconstruction method. This technique consists in the application of a focus measure for every pixel in the stack. An approximation method is used…

[SDE] Environmental Sciences[SDV.SA.AGRO] Life Sciences [q-bio]/Agricultural sciences/Agronomy[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[SDV]Life Sciences [q-bio][SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/AgronomyComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONagronomic scenes[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingcrop analysis[SDV] Life Sciences [q-bio][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[ SDV.SA.AGRO ] Life Sciences [q-bio]/Agricultural sciences/Agronomyacquisition system[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology3D reconstruction[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingComputingMilieux_MISCELLANEOUS[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingComputingMethodologies_COMPUTERGRAPHICS
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Conception de systèmes multi-performants sur la base de systèmes cohérents en œuvre dans des exploitations agricoles

2014

National audience

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio][INFO] Computer Science [cs]culturesélevage[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio]système[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][SHS] Humanities and Social SciencesperformancesComputingMilieux_MISCELLANEOUS
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A modeling approach to evaluate the influence of spatial and temporal structure of an epidemiological surveillance network on the intensity of phytos…

2017

National audience

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio][MATH] Mathematics [math]pesticides[INFO] Computer Science [cs]pest monitoringsimulationdynamic bayesian networks[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio]supervised control[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][SHS] Humanities and Social Sciences[MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS
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Shotgun metagenomics sequencing of the rhizosphere microbiota associated to seven ecotypes of Medicago truncatula

2019

International audience; Healthy plants host a remarkable diversity of microorganisms known as plant microbiota, which provide host services such as pathogen protection and nutrient acquisition. Thus, plant microbiota emerges as a trait that extends the capacity of plants to adapt to their environment. So far, microbial community profiling has mostly allowed the description of the phylogenetic structure of plant microbiota, whereas functional insights were mostly obtained from experiments using model strains. Thus, the plant impact on the microbial functional genes pool in the rhizosphere remains largely unknown. The goals of the study were to (i) compare the functional genes pool of the rhi…

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio]fungifood and beverages[MATH] Mathematics [math][INFO] Computer Science [cs][SDV] Life Sciences [q-bio]Medicago truncatula[SDE]Environmental Sciencesmicrobiota[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][MATH]Mathematics [math]rhizosphere
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Introduction du séminaire. Le projet ANR Peerless : viabilité d’une gestion écologique renforcée de la santé des plantes dans les paysages agricoles

2017

Prod 2017-344a SPE équipe EA GESTAD INRA; International audience; L’enjeu du projet PEERLESS (Appel d’offre ANR agrobiosphere, 2012) est de proposer une gestion viable des populations de ravageurs dans les agroécosystèmes par une approche intégrative combinant différentes échelles spatiales, des cultures pérennes et annuelles et les interactions trophiques entre plusieurs ravageurs et leurs ennemis naturels. La régulation des bioagresseurs par les auxiliaires naturellement présents dans les cultures est le service ecosystèmique que l’on souhaite renforcer afin de diminuer la dépendance des systèmes de production agricole aux pesticides. Bien que ces auxiliaires des cultures soient souvent m…

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio]paysageslutte biologique[MATH] Mathematics [math][INFO] Computer Science [cs]scénarios[SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio][SDE]Environmental Sciencesgestion intégrée de la santé des plantes[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs][SDV.BV] Life Sciences [q-bio]/Vegetal BiologyIntensification écologique[SHS] Humanities and Social Sciences[MATH]Mathematics [math]viabilité socio-économique
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Predicting spread patterns of centrifugal fertiliser spreaders

2014

International audience; Nowadays farmers recognize the importance of a correct and precise fertiliser application: non-uniform spread patterns cause extra pressure on the environment and might result in economic losses for the farmer. In Europe most spreading is done by centrifugal fertilizer spreaders but their spreading process is not easy to monitor and to control. To perform a precise fertilising farmers need proper tools to determine and evaluate the spread pattern at farm level. Therefore the Flemish Institute for Agricultural and Fisheries Research (ILVO) is exploring and developing a fast and accurate technique for measuring the spread pattern of conventional centrifugal spreaders. …

[SDE] Environmental Sciences[SDV]Life Sciences [q-bio]spread patternimage techniques[INFO.INFO-ES] Computer Science [cs]/Embedded Systemsballistic flight;fertiliser[SDV] Life Sciences [q-bio][SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biologycross correlation[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO.INFO-ES]Computer Science [cs]/Embedded Systems[ INFO.INFO-ES ] Computer Science [cs]/Embedded SystemsComputingMilieux_MISCELLANEOUS
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Insertion des légumineuses dans les systèmes de culture : source d’azote symbiotique et de diversification des assolements

2017

National audience

[SDE] Environmental Sciences[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering[SDV]Life Sciences [q-bio][SDV.IDA] Life Sciences [q-bio]/Food engineering[INFO] Computer Science [cs][SHS]Humanities and Social Sciences[SDV] Life Sciences [q-bio][SDE]Environmental Sciences[SDV.IDA]Life Sciences [q-bio]/Food engineering[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering[INFO]Computer Science [cs][SHS] Humanities and Social SciencesComputingMilieux_MISCELLANEOUS
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La recherche publique en France en 2019 : Diagnostic et propositions du Comité national

2019

Projet porté par le Comité National du CNRS.; Dans le contexte de la préparation d’une loi de programmation pluriannuelle de la recherche, ce document présente la contribution du Comité national de la recherche scientifique à l’analyse de la situation de la recherche publique en France, de son évolution récente (depuis la loi LRU de 2008) et de ses perspectives, ainsi qu’un ensemble de propositions qui ont été finalisées et ont fait l’objet d’une approbation solennelle lors de la session plénière du Comité national organisée à Paris le 4 juillet 2019.

[SDE] Environmental Sciences[SPI] Engineering Sciences [physics][SDV]Life Sciences [q-bio][MATH] Mathematics [math][INFO] Computer Science [cs][PHYS] Physics [physics][SHS]Humanities and Social Sciences[SDU] Sciences of the Universe [physics][SPI]Engineering Sciences [physics][SCCO]Cognitive science[CHIM] Chemical Sciences[CHIM]Chemical Sciences[NLIN] Nonlinear Sciences [physics][INFO]Computer Science [cs][NLIN]Nonlinear Sciences [physics][MATH]Mathematics [math]ComputingMilieux_MISCELLANEOUS[PHYS]Physics [physics][QFIN]Quantitative Finance [q-fin][SCCO] Cognitive science[QFIN] Quantitative Finance [q-fin][STAT] Statistics [stat][SDV] Life Sciences [q-bio][STAT]Statistics [stat][SDU]Sciences of the Universe [physics][SDE]Environmental Sciences[SHS] Humanities and Social Sciences[SHS.HIST]Humanities and Social Sciences/History
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Effect of timing of grassland destruction on nitrogen mineralization kinetics.

2007

International audience

[SDE] Environmental Sciencesazotemineralisation[SDV]Life Sciences [q-bio]n fertilisationdestruction de prairie[INFO] Computer Science [cs]n mineralizationrotation[SDV] Life Sciences [q-bio]prairie annuelleprairie temporaire[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biology[INFO]Computer Science [cs]ley-arable rotationgrassland destructionComputingMilieux_MISCELLANEOUS
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Dynamiques de populations en milieu hétérogène : modèles et estimation de paramètres

2017

Prod 2017-344i SPE équipe EA GESTAD INRA; National audience; Cet exposé traite de (i) la modélisation de dynamiques de populations dans des paysages hétérogènes, (ii) la modélisation des paysages eux-mêmes, (iii) l'estimation des paramètres de ces modèles à partir de données d'abondance ou de données génétiques. Nous nous concentrerons sur deux grandes classes de modèles de dynamique des populations : les modèles individu-centrés basés sur des équations différentielles stochastiques, et les modèles de réaction-diffusion. Après une introduction du lien entre ces approches, 5 illustrations issues des projets sont présentées: - modélisation de paysages hétérogènes fragmentés, via l’outil MULTI…

[SDE] Environmental Sciencesmodelisation du paysage[SDV]Life Sciences [q-bio]modeles de reaction-diffusiondonnees genetiquesmodeles discrets/continus;[MATH] Mathematics [math][INFO] Computer Science [cs][SDV] Life Sciences [q-bio]equations aux derivees partiellesmodeles 2d/1d[SDE]Environmental Sciences[SDV.BV]Life Sciences [q-bio]/Vegetal Biology[SDV.BV] Life Sciences [q-bio]/Vegetal Biologyapproches mecanisticostatistiques[INFO]Computer Science [cs]equations differentielles stochastiques[MATH]Mathematics [math]
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