226 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Centre de Recherche en Informatique, Signal et Automatique de LilleFR37 papers
- Université de LilleFR33 papers
- Centre National de la Recherche ScientifiqueFR26 papers
- Centre de Recherche en InformatiqueFR16 papers
- École Centrale de LilleFR13 papers
- Télécom LilleFR10 papers
- Institut Mines-TélécomFR8 papers
- Universidad Carlos III de MadridES5 papers
- University of FlorenceIT5 papers
- Stony Brook UniversityUS4 papers
- Universidad Rey Juan CarlosES4 papers
- Universitat de ValènciaES4 papers
5 papers · 1 filter
DAStatFormer: A Hybrid Multibranch Transformer with Statistical Feature Integration for DAS-Based Pattern Recognitions
Michel Dione, Jerry Lonlac, Hélène Louis +2
Distributed Acoustic Sensing (DAS) enables large-scale monitoring through optical fibers, but its high dimensionality and complex spatio-temporal patterns make event classification…
Maximize margins for robust splicing detection
Julien Simon de Kergunic, Rony Abecidan, Patrick Bas +1
Despite recent progress in splicing detection, deep learning-based forensic tools remain difficult to deploy in practice due to their high sensitivity to training conditions. Even…
Stacking-based deep neural network for player scouting in football 1
Simon Lacan
Datascouting is one of the most known data applications in professional sport, and specifically football. Its objective is to analyze huge database of players in order to detect hi…
Leveraging Data Geometry to Mitigate CSM in Steganalysis
Rony Abecidan, Vincent Itier, Jérémie Boulanger +2
In operational scenarios, steganographers use sets of covers from various sensors and processing pipelines that differ significantly from those used by researchers to train stegana…
Fusion of Physiological and Behavioural Signals on SPD Manifolds with Application to Stress and Pain Detection
Yujin WU, Mohamed Daoudi, Ali Amad +2
Existing multimodal stress/pain recognition approaches generally extract features from different modalities independently and thus ignore cross-modality correlations. This paper pr…