Search results for "APPRENTISSAGE"

showing 10 items of 223 documents

A metabolomic study of yeast/bacteria interactions

2015

As a complex microbial ecosystem, wine is a particularly interesting model for studying interactions between microorganisms. Contact-independent interactions (indirect interactions) between the yeast Saccharomyces cerevisae and the lactic acid bacterium Oenococcus oeni have a direct effect on malolactic fermentation (MLF), induction and completion, which is an important factor in wine quality. Yeast strains could be classified as MLF+ phenotype if it usually stimulates the bacterial growth or MLF- in the opposite case. The known metabolites that stimulate or inhibit the MLF cannot always explain the phenotypic distinction. In this work, a multidisciplinary workflow combining non-targeted me…

UPLC-Q-TOF-MSWineBactérie lactiqueApprentissage automatique[SDV.IDA] Life Sciences [q-bio]/Food engineeringYeastMicrobial interactionInteraction microbienne[SDV.AEN] Life Sciences [q-bio]/Food and NutritionMachine learningVinLactic acid bacteriaMetabolomicsLevurePeptidesFT-ICR-MSMétabolomique
researchProduct

Classification par méthodes d’apprentissage supervisé et faiblement superviséd’images multimodales pour l’aide au diagnostic du lentigo malin en derm…

2021

Carried out in collaboration with the Saint-Étienne University Hospital, this work provides additional information to help the skin diagnosis by providing new decision methods on Lentigo Maligna and Lentigo Maligna Melanoma pathologies. To this end, the modalities regularly used in clinical conditions are made available to this work and are orchestrated within a multimodal process. Among image modalities, may be mentioned the clinical photography, the dermatoscopy, and the confocal reflectance microscopy. Initially, the first steps of this manuscript focus on reflectance confocal microscopy as the work in computer diagnostic assistance is relatively underdeveloped, in particular on the dete…

Upervised learning[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]Apprentissage profond[INFO.INFO-TS] Computer Science [cs]/Signal and Image ProcessingLentigo Maligna MelanomaImage classification[INFO.INFO-IM] Computer Science [cs]/Medical ImagingDermatoscopieDermatologyMultimodalité[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Dermatoscopy[INFO.INFO-IM]Computer Science [cs]/Medical ImagingApprentissage faiblement superviséMultimodalityDermatologieFusion de donnéesWeakly supervised learningLentigo MalignaDeep learningApprentissage superviséData fusionMicroscopie confocale par réflectanceClassification d'images[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]Confocal reflectance microscopySupervised learning
researchProduct

Olores, aprendizaje y periodos sensibles durante el desarrollo

2010

traduction simultanée du titre; absent

[ SDV.NEU.PC ] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior[SDV.AEN] Life Sciences [q-bio]/Food and Nutrition[SDV.NEU.PC]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behavior[ SDV.AEN ] Life Sciences [q-bio]/Food and Nutrition[SDV.NEU.PC] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/Psychology and behaviorodeur[SDV.AEN]Life Sciences [q-bio]/Food and Nutritionapprentissagedéveloppement
researchProduct

Federated Learning for Zero-Day Attack Detection in 5G and Beyond V2X Networks

2023

Deploying Connected and Automated Vehicles (CAVs) on top of 5G and Beyond networks (5GB) makes them vulnerable to increasing vectors of security and privacy attacks. In this context, a wide range of advanced machine/deep learning-based solutions have been designed to accurately detect security attacks. Specifically, supervised learning techniques have been widely applied to train attack detection models. However, the main limitation of such solutions is their inability to detect attacks different from those seen during the training phase, or new attacks, also called zero-day attacks. Moreover, training the detection model requires significant data collection and labeling, which increases th…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]5GBIoV[INFO.INFO-NI] Computer Science [cs]/Networking and Internet Architecture [cs.NI]Zero-day attacksSécurité5G V2X IoV Sécurité Attaques Détection Apprentissage Fédéré[INFO] Computer Science [cs]Intrusion DetectionDétectionAttaquesSecurityV2XApprentissage FédéréFederated Learning5GConnected and Automated Vehicles[INFO.INFO-CR] Computer Science [cs]/Cryptography and Security [cs.CR]
researchProduct

Application of LSTM architectures for next frame forecasting in Sentinel-1 images time series

2020

L'analyse prédictive permet d'estimer les tendances des évènements futurs. De nos jours, les algorithmes Deep Learning permettent de faire de bonnes prédictions. Cependant, pour chaque type de problème donné, il est nécessaire de choisir l'architecture optimale. Dans cet article, les modèles Stack-LSTM, CNN-LSTM et ConvLSTM sont appliqués à une série temporelle d'images radar sentinel-1, le but étant de prédire la prochaine occurrence dans une séquence. Les résultats expérimentaux évalués à l'aide des indicateurs de performance tels que le RMSE et le MAE, le temps de traitement et l'index de similarité SSIM, montrent que chacune des trois architectures peut produire de bons résultats en fon…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI]FOS: Computer and information sciencesApprentissage profondComputer Science - Machine LearningImage and Video Processing (eess.IV)[INFO.INFO-NE] Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]PrévisionComputer Science - Neural and Evolutionary ComputingDeep Learning AlgorithmsPrédiction[INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]Electrical Engineering and Systems Science - Image and Video ProcessingLand cover change[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Machine Learning (cs.LG)SARIMA[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]FOS: Electrical engineering electronic engineering information engineeringSatellite imagesNeural and Evolutionary Computing (cs.NE)LSTMPredictionForecastingImages satellitaires
researchProduct

Optimisation et implémentation de méthodes bio-inspirées d'extraction de caractéristiques pour la reconnaissance d'objets visuels

2016

Industry has growing needs for so-called “intelligent systems”, capable of not only ac-quire data, but also to analyse it and to make decisions accordingly. Such systems areparticularly useful for video-surveillance, in which case alarms must be raised in case ofan intrusion. For cost saving and power consumption reasons, it is better to perform thatprocess as close to the sensor as possible. To address that issue, a promising approach isto use bio-inspired frameworks, which consist in applying computational biology modelsto industrial applications. The work carried out during that thesis consisted in select-ing bio-inspired feature extraction frameworks, and to optimize them with the aim t…

[INFO.INFO-AI] Computer Science [cs]/Artificial Intelligence [cs.AI][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Bio-inspiréApprentissage automatiqueIntelligence artificielle[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Descripteurs[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]EmbarquéAlgorithm-architecture matching[ INFO.INFO-BI ] Computer Science [cs]/Bioinformatics [q-bio.QM]Vision par ordinateurMachine learningRéseaux de neuronesComputer vision[INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM][ INFO.INFO-AI ] Computer Science [cs]/Artificial Intelligence [cs.AI]OptimisationsFPGANeural networks[INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
researchProduct

Apprentissage incrémental pour la détection de chute de personnes âgées

2015

International audience; Dans ce papier, nous proposons une méthodologie d'évolution supervisée d'un modèle de classification, spécifique à un système de détection de chute de personnes mis au point précédemment. Cette méthodologie met en oeuvre la méthode de détection, un protocole d'apprentissage incrémental ou évolutif, et une méthode d'évaluation et de comparaison des performances, devant conduire à une amélioration des capacités de détection de chutes sur un système embarqué de type caméra intelligente.

[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Détection de Chute[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]apprentissage incrémental.temps réel[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]
researchProduct

Discovering human mobility from mobile data : probabilistic models and learning algorithms

2020

Smartphone usage data can be used to study human indoor and outdoor mobility. In our work, we investigate both aspects in proposing machine learning-based algorithms adapted to the different information sources that can be collected.In terms of outdoor mobility, we use the collected GPS coordinate data to discover the daily mobility patterns of the users. To this end, we propose an automatic clustering algorithm using the Dirichlet process Gaussian mixture model (DPGMM) so as to cluster the daily GPS trajectories. This clustering method is based on estimating probability densities of the trajectories, which alleviate the problems caused by the data noise.By contrast, we utilize the collecte…

[INFO.INFO-OH] Computer Science [cs]/Other [cs.OH]Machine LearningDeep LearningDonnées mobiles[INFO.INFO-OH]Computer Science [cs]/Other [cs.OH]Variational InferenceApprentissage machineMobile DataProbabilistic Models
researchProduct

« Apprendre à apprendre » : quels enjeux pour les apprenants et les enseignants ?

2019

International audience

[SCCO.NEUR]Cognitive science/Neuroscience[SCCO.NEUR] Cognitive science/Neuroscience[SCCO.PSYC] Cognitive science/Psychology[SCCO.PSYC]Cognitive science/PsychologyMéthodes d’apprentissageComputingMilieux_MISCELLANEOUSNeuromythesApprendre à apprendre
researchProduct

Hollywood et l’ergonomie des vidéos pour la formation: Effet de la continuité des points de vue de la caméra dans l’apprentissage d’une procédure méd…

2021

International audience; La conception de vidéos éducatives selon des principes cinématographiques peut affecter leur efficacité potentielle pour l'apprentissage. L'objectif de la présente expérience était d'étudier l'effet de la continuité filmique dans l'apprentissage d'une procédure médicale dans la formation aux soins infirmiers. Nous avons testé l'effet de la violation de la règle des 180° qui propose que la caméra doit rester du même côté d'un axe imaginaire de 180° lorsqu'un événement en cours est filmé. Dans une expérience de type pré-post tests, 56 étudiants en soins infirmiers ont été répartis en deux groupes pour apprendre une procédure de réanimation cardiopulmonaire à partir d'u…

[SCCO.PSYC] Cognitive science/Psychology[SCCO.PSYC]Cognitive science/PsychologyApprentissage de procédurepoints de vue caméravidéosattention
researchProduct