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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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Henning Wachsmuth, Gabriella Lapesa, Elena Cabrio, Anne Lauscher, Joonsuk Park, et al.. Argument Quality Assessment in the Age of Instruction-Following Large Language Models. Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC/COLING 2024, May 2024, Torino, Italy. ⟨hal-04787971⟩
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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⟩
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Anca-Ioana Grapa, Georgios Efthymiou, Ellen van Obberghen-Schilling, Laure Blanc-Féraud, Xavier Descombes. A spatial statistical framework for the parametric study of fiber networks: application to fibronectin deposition by normal and activated fibroblasts. Biological Imaging, In press, ⟨10.1017/S2633903X23000247⟩. ⟨hal-04320315v2⟩
Documents en texte intégral
703
Notices
311
Statistiques par discipline
Mots clés
OPAL-Meso
MRI
Convergence analysis
Image fusion
Macroscopic traffic flow models
Electrocardiogram
Fluorescence microscopy
RDF
Healthcare
Graph signal processing
Correlation matrices
Topological Data Analysis
Spiking neural networks
Segmentation
Arguments
Biomarkers
Linked data
Clustering
Extracellular matrix
Multi-Agent Systems
Sparsity
CNN
Data augmentation
Privacy
Web of Things
Grammatical Evolution
Excursion sets
Ontology Learning
Change point detection
Hyperbolic systems of conservation laws
Semantic Web
Autonomous vehicles
Adversarial classification
Autoencoder
Anomaly detection
Hyperspectral data
Spiking Neural Networks
Atrial Fibrillation
Isomanifolds
Brain-inspired computing
COVID-19
Argument mining
Argument Mining
Apprentissage profond
Predictive model
Extreme value theory
Latent block model
Convolutional neural networks
Echocardiography
NLP Natural Language Processing
Diffusion strategy
Distributed optimization
Federated learning
Deep Learning
Information Extraction
Knowledge graph
Semantic segmentation
Diffusion MRI
Electrophysiology
Co-clustering
Machine learning
Artificial intelligence
Super-resolution
Dimensionality reduction
Knowledge graphs
Persistent homology
Semantic web
Clinical trials
Artificial Intelligence
Linked Data
FPGA
Computing methodologies
Coxeter triangulation
Graph neural networks
Uncertainty
Federated Learning
Unsupervised learning
Visualization
Consensus
Dense labeling
Neural networks
SPARQL
Deep learning
Contrastive learning
ECG
Image segmentation
Computational Topology
53B20
Domain adaptation
Cable-driven parallel robot
Differential privacy
Alzheimer's disease
Computer vision
Explainable AI
Chernoff information
Geometric graphs
Atrial fibrillation
Optimization
Convolutional neural network
Convolutional Neural Networks