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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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Alberto Ibarrondo Luis, Ismet Kerenciler, Hervé Chabanne, Vincent Despiegel, Melek Önen. Monchi: Multi-scheme Optimization For Collaborative Homomorphic Identification. IH&MMSec 2024, 12th ACM Workshop on Information Hiding and Multimedia Security, ACM, Jun 2024, Baiona, Spain. ⟨10.1145/3658664.3659633⟩. ⟨hal-04562874⟩
Documents en texte intégral
646
Notices
300
Statistiques par discipline
Mots clés
Semantic web
Computational Topology
Medical imaging
Super-resolution
Spiking Neural Networks
Federated Learning
Fluorescence microscopy
Deep learning
Image segmentation
Convolutional neural networks
Clinical trials
Co-clustering
Alzheimer's disease
Web of Things
NLP Natural Language Processing
Dense labeling
53B20
Linked data
Uncertainty
Arguments
Linked Data
Event cameras
Diffusion MRI
Contrastive learning
Electrophysiology
Atrial fibrillation
FPGA
Latent block model
Binary image
MRI
Ontology Learning
Excursion sets
Echocardiography
Segmentation
Differential privacy
Semantic Web
Cable-driven parallel robot
OPAL-Meso
Electrocardiogram
Predictive model
Argument Mining
Embedded Systems
Convolutional Neural Networks
Convergence analysis
Domain adaptation
Artificial Intelligence
Dimensionality reduction
Grammatical Evolution
Sparsity
Privacy
Extreme value theory
Information Extraction
Healthcare
Autonomous vehicles
Explainable AI
Hyperspectral data
Image fusion
Knowledge graph
Computing methodologies
Autoencoder
Convolutional neural network
Neural networks
Electronic medical record
Anomaly detection
Visualization
Multi-Agent Systems
Consensus
Atrial Fibrillation
Isomanifolds
Deep Learning
Topological Data Analysis
Clustering
Knowledge graphs
Distributed optimization
Multiple Sclerosis
Optimization
SPARQL
Graph neural networks
Physics-based learning
Coxeter triangulation
Extracellular matrix
Apprentissage profond
Data augmentation
Persistent homology
Unsupervised learning
Brain-inspired computing
COVID-19
RDF
Diffusion strategy
Semantic segmentation
Artificial intelligence
Machine learning
Crossings
CNN
Simulations
Biomarkers
Spiking neural networks
Hyperbolic systems of conservation laws
Macroscopic traffic flow models
Computer vision