Loading...
3IA Côte d'Azur - Interdisciplinary Institute for Artificial Intelligence
3IA Côte d'Azur is one of the four "Interdisciplinary Institutes for Artificial Intelligence" that were created in France in 2019. Its ambition is to create an innovative ecosystem that is influential at the local, national and international level. The 3IA Côte d'Azur institute is led by Université Côte d'Azur in partnership with major higher education and research partners in the region of Nice and Sophia Antipolis: CNRS, Inria, INSERM, EURECOM, and SKEMA Business School. The 3IA Côte d'Azur institute is also supported by ECA, Nice University Hospital Center (CHU Nice), CSTB, CNES, Data ScienceTech Institute and INRAE. The project has also secured the support of more than 62 companies and start-ups.
Last Deposits
Documents in Full Text
695
Notices
307
Statistics by Discipline
Keywords
Contrastive learning
ECG
Computer vision
Apprentissage profond
CNN
Embedded Systems
FPGA
Unsupervised learning
Clinical trials
Healthcare
Linked Data
Convergence analysis
Multi-Agent Systems
Data augmentation
Argument Mining
Extracellular matrix
Diffusion strategy
Correlation matrices
NLP Natural Language Processing
Geometric graphs
Persistent homology
Deep Learning
Anomaly detection
Dense labeling
Brain-inspired computing
Image segmentation
Consensus
Clustering
Ontology Learning
Deep learning
Hyperbolic systems of conservation laws
Electrophysiology
RDF
Semantic web
Federated learning
Cable-driven parallel robot
Image fusion
MRI
Atrial Fibrillation
Privacy
Linked data
Artificial intelligence
Change point detection
Spiking Neural Networks
Visualization
Explainable AI
Coxeter triangulation
Differential privacy
Convolutional neural network
Latent block model
Web of Things
Knowledge graphs
Echocardiography
Argument mining
Artificial Intelligence
Computing methodologies
Electronic medical record
Isomanifolds
53B20
Alzheimer's disease
Domain adaptation
Semantic Web
Computational Topology
Autonomous vehicles
OPAL-Meso
Segmentation
Excursion sets
Distributed optimization
SPARQL
Knowledge graph
Diffusion MRI
Biomarkers
Semantic segmentation
Hyperspectral data
Machine learning
Topological Data Analysis
COVID-19
Co-clustering
Convolutional Neural Networks
Fluorescence microscopy
Federated Learning
Atrial fibrillation
Arguments
Autoencoder
Super-resolution
Graph neural networks
Convolutional neural networks
Sparsity
Predictive model
Neural networks
Macroscopic traffic flow models
Graph signal processing
Spiking neural networks
Electrocardiogram
Grammatical Evolution
Dimensionality reduction
Optimization
Extreme value theory
Information Extraction
Uncertainty