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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. Explainable Electrocardiogram Analysis with Wave Decomposition: Application to Myocardial Infarction Detection. STACOM 2022 - 13th workshop on Statistical Atlases and Computational Models of the Heart, Sep 2022, Singapore, Singapore. ⟨hal-03888791v2⟩
Documents en texte intégral
652
Notices
301
Statistiques par discipline
Mots clés
Electrophysiology
Isomanifolds
Convolutional Neural Networks
Computational Topology
Co-clustering
Cable-driven parallel robot
Excursion sets
Topological Data Analysis
NLP Natural Language Processing
Atrial Fibrillation
Fibronectin
Medical imaging
Differential privacy
Anomaly detection
Ontology Learning
Image segmentation
Diffusion strategy
Privacy
Image fusion
Electrocardiogram
Machine learning
Semantic web
Linked data
Argument Mining
Neural networks
Convolutional neural networks
53B20
Information Extraction
Multiple Sclerosis
Deep Learning
Coxeter triangulation
Extracellular matrix
MRI
Healthcare
Diffusion MRI
SPARQL
Computing methodologies
Sparsity
Hyperbolic systems of conservation laws
Persistent homology
Atrial fibrillation
Super-resolution
Optimization
Brain-inspired computing
Latent block model
OPAL-Meso
Biomarkers
Distributed optimization
Artificial intelligence
Convolutional neural network
Knowledge graph
Electronic medical record
CNN
Arguments
Autoencoder
Deep learning
Multi-Agent Systems
Dense labeling
COVID-19
FPGA
Artificial Intelligence
Segmentation
Federated Learning
Alzheimer's disease
Spiking Neural Networks
Extreme value theory
Dimensionality reduction
Convergence analysis
Grammatical Evolution
Spiking neural networks
Computer vision
Data augmentation
Autonomous vehicles
Domain adaptation
Knowledge graphs
Apprentissage profond
Contrastive learning
Consensus
Hyperspectral data
Linked Data
Event cameras
Uncertainty
Graph neural networks
Fluorescence microscopy
Echocardiography
Unsupervised learning
Clinical trials
Macroscopic traffic flow models
Semantic segmentation
Federated learning
Visualization
Explainable AI
Semantic Web
Simulations
RDF
Clustering
Embedded Systems
Predictive model
Web of Things
Physics-based learning