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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
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Yingyu Yang, Marie Rocher, Pamela Moceri, Maxime Sermesant. Uncertainty-Based Multi-modal Learning for Myocardial Infarction Diagnosis Using Echocardiography and Electrocardiograms. The 5th International Workshop of Advances in Simplifying Medical UltraSound (ASMUS), Oct 2024, Marrakech, Morocco. pp.177-186, ⟨10.1007/978-3-031-73647-6_17⟩. ⟨hal-04776612⟩
Documents en texte intégral
701
Notices
311
Statistiques par discipline
Mots clés
Information Extraction
53B20
Knowledge graphs
Isomanifolds
Extracellular matrix
Cable-driven parallel robot
Linked data
Predictive model
Web of Things
Graph signal processing
RDF
Autonomous vehicles
Contrastive learning
Semantic web
Argument Mining
Differential privacy
Convolutional neural network
Dense labeling
Anomaly detection
Clinical trials
Excursion sets
MRI
SPARQL
Hyperspectral data
Biomarkers
Neural networks
Electronic medical record
ECG
Spiking Neural Networks
Embedded Systems
Semantic Web
Ontology Learning
Extreme value theory
Geometric graphs
Machine learning
Convolutional neural networks
Diffusion strategy
Data augmentation
Domain adaptation
Latent block model
Brain-inspired computing
Echocardiography
Sparsity
Hyperbolic systems of conservation laws
Electrocardiogram
Co-clustering
Spiking neural networks
Knowledge graph
Fluorescence microscopy
Topological Data Analysis
Convergence analysis
Change point detection
Autoencoder
Apprentissage profond
Image fusion
Coxeter triangulation
Artificial Intelligence
Image segmentation
NLP Natural Language Processing
Atrial fibrillation
Visualization
Explainable AI
Macroscopic traffic flow models
Super-resolution
Convolutional Neural Networks
Distributed optimization
Artificial intelligence
Federated learning
Clustering
Optimization
COVID-19
Persistent homology
Healthcare
Segmentation
Dimensionality reduction
Arguments
Deep learning
Privacy
Deep Learning
Argument mining
Linked Data
Computational Topology
Graph neural networks
Diffusion MRI
Electrophysiology
Federated Learning
Alzheimer's disease
Computing methodologies
Computer vision
Grammatical Evolution
Atrial Fibrillation
Consensus
Semantic segmentation
Correlation matrices
FPGA
OPAL-Meso
Unsupervised learning
CNN
Multi-Agent Systems
Uncertainty