15 citations
- Laure Berti-Équille3 profiles8 · h 24
- Jérémie Guiochet2 profiles3 · h 22
- Joris Guérin3 · h 2
- Kevin Delmas3 · h 5
- K. Veeramachaneni3 · h 38
- Sarah Alnegheimish3 · h 9
- Grigor Bezirganyan2 · h 3
- Raul Sena Ferreira2 · h 5
- Sana Sellami2 · h 3
- Sébastien Fournier2 · h 4
- Abdelmadjid Chergui1 · h 1
- Alfredo Cuesta-Infante1 · h 14
- Institut de Recherche pour le DéveloppementFR13 papers
- Acteurs, Ressources et Territoires dans le DéveloppementFR11 papers
- Laboratoire d'Analyse et d'Architecture des SystèmesFR3 papers
- Office National d'Études et de Recherches AérospatialesFR3 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR3 papers
- Aix-Marseille UniversitéFR2 papers
- IAC (United States)US2 papers
- Université Toulouse III - Paul SabatierFR2 papers
- Centre National de la Recherche ScientifiqueFR1 paper
- Délégation Provence et CorseFR1 paper
- Département Traitement de l’Information et SystèmesFR1 paper
- Hamad bin Khalifa UniversityQA1 paper
14 papers
MixMAS: A Framework for Sampling-Based Mixer Architecture Search for Multimodal Fusion and Learning
Abdelmadjid Chergui, Grigor Bezirganyan, Sana Sellami +2
Choosing a suitable deep learning architecture for multimodal data fusion is a challenging task, as it requires the effective integration and processing of diverse data types, each…
Hierarchical Classification for Automated Image Annotation of Coral Reef Benthic Structures
Célia Blondin, Joris Guérin, Kelly Inagaki +2
Automated benthic image annotation is crucial to efficiently monitor and protect coral reefs against climate change. Current machine learning approaches fail to capture the hierarc…
Safety Monitoring of Machine Learning Perception Functions: a Survey
Raul Sena Ferreira, Joris Guérin, Kevin Delmas +2
Machine Learning (ML) models, such as deep neural networks, are widely applied in autonomous systems to perform complex perception tasks. New dependability challenges arise when ML…
Multimodal Learning with Uncertainty Quantification based on Discounted Belief Fusion
Grigor Bezirganyan, Sana Sellami, Laure Berti-Équille +1
Multimodal AI models are increasingly used in fields like healthcare, finance, and autonomous driving, where information is drawn from multiple sources or modalities such as images…
Can we Defend Against the Unknown? An Empirical Study About Threshold Selection for Neural Network Monitoring
Khoi Tran Dang, Kevin Delmas, Jérémie Guiochet +1
With the increasing use of neural networks in critical systems, runtime monitoring becomes essential to reject unsafe predictions during inference. Various techniques have emerged…
Large language models can be zero-shot anomaly detectors for time series?
Sarah Alnegheimish, Linh Nguyen, Laure Berti-Equille +1
Recent studies have shown the ability of large language models to perform a variety of tasks, including time series forecasting. The flexible nature of these models allows them to…