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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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Alessandro Viani, Boris A Gutman, Emile d'Angremont, Marco Lorenzi. Disease Progression Modelling and Stratification for detecting sub-trajectories in the natural history of pathologies: application to Parkinson's Disease trajectory modelling. Longitudinal Disease Tracking and Modelling with Medical Images and Data, Oct 2024, Marrachech, Morocco. ⟨hal-04833565⟩
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Javier Villar-Valero, Jesus Jairo Rodríguez Padilla, Buntheng Ly, Juan F Gomez, Mihaela Pop, et al.. Exploring Chemotherapy-Induced Cardiotoxicity Combining A 3D Computational Model and Preclinical Cardiac Imaging Data. MICCAI 2024, STACOM Workshop, Oct 2024, Marrakesh, Maroc, Morocco. ⟨hal-04840698⟩
Documents en texte intégral
735
Notices
332
Statistiques par discipline
Mots clés
Extracellular matrix
NLP Natural Language Processing
Co-clustering
Linked data
Graph signal processing
Medical imaging
Latent block model
Image fusion
Convolutional neural network
Domain adaptation
Distributed optimization
Topological Data Analysis
Contrastive learning
RDF
FDG PET
Hyperbolic systems of conservation laws
Computational Topology
OPAL-Meso
Knowledge graphs
SPARQL
Extreme value theory
MRI
Caching
Brain-inspired computing
Autoencoder
Explainable AI
Diffusion MRI
Electrocardiogram
53B20
Computer vision
Change point detection
Sparsity
Consensus
Atrial Fibrillation
Apprentissage profond
SHACL
Coxeter triangulation
Ontology Learning
Clustering
Geometric graphs
Autonomous vehicles
Computing methodologies
Super-resolution
Segmentation
Argument Mining
FPGA
Neural networks
Federated Learning
Arguments
Knowledge graph
Federated learning
Anomaly detection
Isomanifolds
Information Extraction
Chernoff information
Adversarial classification
Artificial intelligence
Fluorescence microscopy
Atrial fibrillation
Artificial Intelligence
Spiking neural networks
Argument mining
Electrophysiology
Uncertainty
Excursion sets
Web of Things
Dense labeling
Deep learning
Unsupervised learning
Linked Data
Deep Learning
Hyperspectral data
Spiking Neural Networks
Machine learning
Cable-driven parallel robot
Clinical trials
Visualization
Privacy
Healthcare
Multi-Agent Systems
Convergence analysis
Semantic web
Optimization
Convolutional neural networks
Image segmentation
Convolutional Neural Networks
Alzheimer's disease
Predictive model
NLP
Semantic Web
Grammatical Evolution
COVID-19
Graph neural networks
Echocardiography
Biomarkers
Diffusion strategy
Semantic segmentation
CNN
Persistent homology
Macroscopic traffic flow models