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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
Ran Ran, Liang-Jian Deng, Tai-Xiang Jiang, Jin-Fan Hu, Jocelyn Chanussot, et al.. GuidedNet: A General CNN Fusion Framework via High-Resolution Guidance for Hyperspectral Image Super-Resolution. IEEE Transactions on Cybernetics, 2023, 53 (7), pp.4148-4161. ⟨10.1109/TCYB.2023.3238200⟩. ⟨hal-04473668⟩
Collaborations
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Keywords
Optimization
Deep learning DL
Deep Learning
Digital public health
Computer vision
Classification
Artificial Intelligence AI
Evaluation
Unsupervised learning
Community detection
Chronic obstructive pulmonary disease
Object detection
Data visualization
Dictionaries
Adherence
Speech synthesis
Agriculture
Neural networks
Brain
Alternating direction method of multipliers ADMM
Data models
Stabilization
Training
Detectors
Speech production
Online learning
Sleep apnea
Prediction
Continuous positive airway pressure
Kernel methods
Representation learning
Nash equilibrium
Hyperspectral imaging
Convex optimization
Data mining
Manifold learning
Image reconstruction
Alternating direction method of multipliers
Remote sensing
Co-design
Pansharpening
Attention mechanism
Multispectral
Speech motor control
Feature extraction
Endmember variability
Big data
Remote sensing RS
Agricultural exposome
Generative models
Artificial Intelligence
Scheduling
Hyperspectral image
Convolution
Semantic segmentation
Stochastic differential equations
Artificial intelligence
CPAP
Intelligence artificielle
Privacy
Dimensionality reduction
Asymptotic stability
Super-resolution
Sparsity
AI Governance
Stochastic approximation
Image fusion
Convolutional neural networks
COVID-19
Ethics
Fairness
Biometrics
Infinite-dimensional systems
Variational inference
Random matrix theory
Data fusion
AI
Machine learning
Spatial resolution
Anomaly detection
Optimal control
Europe
Machine Learning
Deep learning
Affect stories
Backstepping
Obstructive sleep apnea
Digital health e-health
Tensors
Éthique
Asymptotic normality
Algorithmes
Spectral clustering
Audio-visual speech enhancement
Task analysis
Hyperspectral
Air pollution
Output feedback
Automatic speech recognition
Adaptation models