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MIAI Grenoble Alpes (Multidisciplinary Institute in Artificial Intelligence) aims to conduct research in artificial intelligence at the highest level, to offer attractive courses for students and professionals of all levels, to support innovation in large companies, SMEs and startups and to inform and interact with citizens on all aspects of AI.
The activities of MIAI Grenoble Alpes are structured around two main themes : future AI systems and AI for human beings the environment.
Instructions to authors: If your research work has been supported by the MIAI Grenoble Alpes, please mention in your article: "This work has been partially supported by MIAI@Grenoble Alpes, (ANR-19-P3IA-0003)."
Derniers dépôts
Roberto Dragone, Giorgio Licciardi, Gerardo Grasso, Costantino del Gaudio, Jocelyn Chanussot. Analysis of the Chemical and Physical Environmental Aspects that Promoted the Spread of SARS-CoV-2 in the Lombard Area. International Journal of Environmental Research and Public Health, 2021, 18 (3), pp.1226. ⟨10.3390/ijerph18031226⟩. ⟨hal-03429704⟩
Collaborations
Number of fulltexts
977
Number of references
628
Keywords
Semantic segmentation
Multispectral
Deep learning DL
Machine learning
Innovation
Algorithmes
Computer vision
Prediction
Convolution
Online learning
Feature extraction
Audio-visual speech enhancement
Brain
Data fusion
Tensors
Autism
Spectral clustering
Remote sensing RS
Privacy
Telemonitoring
Continuous positive airway pressure
Representation learning
Variational inference
Remote sensing
Sex differences
Predictive coding
Optimal control
Nash equilibrium
Hyperspectral image
Image fusion
Digital public health
Artificial Intelligence
Evaluation
Manifold learning
Ethics
Random matrix theory
Data mining
Training
Deep learning
Infinite-dimensional systems
Alternating direction method of multipliers ADMM
Speech motor control
Classification
Object detection
Speech production
Image processing
Convex optimization
Endmember variability
Hyperspectral
Data analysis
AI
Correlation
Data models
Image segmentation
Dimensionality reduction
Kernel methods
Convolutional neural networks
Éthique
Backstepping
Deep Learning
Generative models
Intelligence artificielle
Detectors
Asymptotic stability
Stabilization
Big data
Co-design
Output feedback
Santé numérique
Super-resolution
Optimization
Speech synthesis
Optimal controller
Chronic obstructive pulmonary disease
Stochastic approximation
Dictionaries
Fairness
Self-supervised learning
COVID-19
Sleep apnea
Philosophie des techniques
Task analysis
Digital health e-health
EHealth
Scheduling
Spatial frequencies
Spatial resolution
Stochastic differential equations
Simulation
Image reconstruction
Artificial intelligence
OSA
Neural networks
Automatic speech recognition
Hyperspectral imaging
Machine Learning
Unsupervised learning
Pansharpening
Adherence
Ethique de l'intelligence artificielle