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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
704
Notices
311
Statistiques par discipline
Mots clés
Computing methodologies
Computer vision
Cable-driven parallel robot
Apprentissage profond
Super-resolution
Coxeter triangulation
Chernoff information
Domain adaptation
Clustering
Sparsity
Diffusion strategy
CNN
SPARQL
Graph neural networks
Distributed optimization
Fluorescence microscopy
Brain-inspired computing
FPGA
Computational Topology
Topological Data Analysis
Convolutional Neural Networks
Dense labeling
Diffusion MRI
Grammatical Evolution
Ontology Learning
Argument mining
Semantic web
Co-clustering
Clinical trials
Contrastive learning
Echocardiography
RDF
Dimensionality reduction
Deep learning
Knowledge graph
Change point detection
Alzheimer's disease
Linked Data
Spiking Neural Networks
Convergence analysis
Knowledge graphs
Federated learning
Web of Things
Neural networks
Excursion sets
Isomanifolds
NLP Natural Language Processing
Hyperbolic systems of conservation laws
Information Extraction
Hyperspectral data
COVID-19
Geometric graphs
Linked data
Atrial Fibrillation
Spiking neural networks
Visualization
MRI
Artificial intelligence
ECG
Graph signal processing
Convolutional neural networks
Machine learning
Arguments
Persistent homology
Anomaly detection
Data augmentation
Latent block model
Explainable AI
Deep Learning
Adversarial classification
Healthcare
Unsupervised learning
OPAL-Meso
Autoencoder
Predictive model
Privacy
Extracellular matrix
Atrial fibrillation
Correlation matrices
Electrophysiology
Segmentation
Federated Learning
Biomarkers
Argument Mining
Image segmentation
53B20
Macroscopic traffic flow models
Image fusion
Extreme value theory
Multi-Agent Systems
Autonomous vehicles
Differential privacy
Convolutional neural network
Semantic segmentation
Electrocardiogram
Artificial Intelligence
Optimization
Uncertainty
Consensus
Semantic Web