Deep Learning for steganalysis is better than a Rich Model with an Ensemble Classifier, and is natively robust to the cover source-mismatch. - Lionel Pibre; Jérôme Pasquet; Dino Ienco; Marc Chaumont (CoRR, 2015)

Deep learning is a good steganalysis tool when embedding key is reused for different images, even if there is a cover sourcemismatch. - Lionel Pibre; Jérôme Pasquet; Dino Ienco; Marc Chaumont (Media Watermarking, Security, and Forensics, 2016)

How to deal with multi-source data for tree detection based on deep learning. - Lionel Pibre; Marc Chaumont; Gérard Subsol; Dino Ienco; Mustapha Derras (GlobalSIP, 2017)

Localisation d'objets urbains à partir de sources multiples dont des images aériennes. (Localization of urban objects from multiple sources, including aerial imagery). - Lionel Pibre (2018)

Audio-Video detection of the active speaker in meetings. - Francisco Madrigal; Frédéric Lerasle; Lionel Pibre; Isabelle Ferrané (ICPR, 2020)

Automatic macro segmentation into interaction sequence: a silence-based approach for meeting structuring. - Lionel Pibre; Sélim Mechrouh; Thomas Pellegrini; Julien Pinquier; Isabelle Ferrané (CBMI, 2021)

New Active Learning Approach for Seabed Segmentation. - Lionel Pibre; Jérôme Pasquet; Vincent Douzal; Claire Noël (ICIP, 2022)

Audio-video fusion strategies for active speaker detection in meetings. - Lionel Pibre; Francisco Madrigal; Cyrille Equoy; Frédéric Lerasle; Thomas Pellegrini; Julien Pinquier; Isabelle Ferrané (Multim. Tools Appl., 2023)

Boxes to Segmentation to Boxes Again for a Better Detection. - Théo Oriol; Lionel Pibre; Jérôme Pasquet; Zamirddine Mari (IPTA, 2024)