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3IA Côte d'Azur - Interdisciplinary Institute for Artificial Intelligence
3IA Côte d'Azur est l'un des quatre "Instituts interdisciplinaires d'intelligence artificielle" créés en France en 2019. Son ambition est de créer un écosystème innovant et influent au niveau local, national et international. L'institut 3IA Côte d'Azur est piloté par Université Côte d'Azur en partenariat avec les grands partenaires de l'enseignement supérieur et de la recherche de la région niçoise et de Sophia Antipolis : CNRS, Inria, INSERM, EURECOM, SKEMA Business School. L'institut 3IA Côte d'Azur est également soutenu par l'ECA, le CHU de Nice, le CSTB, le CNES, l'Institut Data ScienceTech et l'INRAE. Le projet a également obtenu le soutien de plus de 62 entreprises et start-ups.
Derniers dépôts
Documents en texte intégral
643
Notices
300
Statistiques par discipline
Mots clés
Spiking Neural Networks
Binary image
Data augmentation
Latent block model
Extracellular matrix
Co-clustering
Hyperspectral data
Grammatical Evolution
Coxeter triangulation
Brain-inspired computing
Domain adaptation
COVID-19
Differential privacy
Excursion sets
Federated learning
MRI
53B20
Biomarkers
Medical imaging
Super-resolution
Crossings
Federated Learning
Electrophysiology
Multiple Sclerosis
Semantic web
Dimensionality reduction
Artificial Intelligence
Information Extraction
Extreme value theory
Computing methodologies
Ontology Learning
Web of Things
Topological Data Analysis
Image fusion
Autonomous vehicles
Anomaly detection
Knowledge graph
RDF
Macroscopic traffic flow models
Dense labeling
Segmentation
Multi-Agent Systems
Simulations
CNN
Semantic segmentation
Hyperbolic systems of conservation laws
Healthcare
Convolutional Neural Networks
Atrial Fibrillation
Neural networks
Uncertainty
Electronic medical record
Clinical trials
Embedded Systems
Knowledge graphs
Clustering
Graph neural networks
Cable-driven parallel robot
Artificial intelligence
Explainable AI
Privacy
NLP Natural Language Processing
Apprentissage profond
Linked Data
Deep Learning
Predictive model
Visualization
Autoencoder
Argument Mining
Sparsity
Electrocardiogram
Image segmentation
Atrial fibrillation
Contrastive learning
Distributed optimization
Deep learning
Alzheimer's disease
Echocardiography
Physics-based learning
Convolutional neural networks
Isomanifolds
Unsupervised learning
Persistent homology
Optimization
Diffusion strategy
Linked data
Machine learning
Convergence analysis
OPAL-Meso
Convolutional neural network
Semantic Web
Fluorescence microscopy
Computational Topology
Consensus
Computer vision
Diffusion MRI
FPGA
Arguments
Spiking neural networks
Event cameras