Deep Analysis of CNN Settings for New Cancer Whole-slide Histological Images Segmentation: The Case of Small Training Sets. - Sonia Mejbri; Camille Franchet; Ismat Ara Reshma; Josiane Mothe; Pierre Brousset; Emmanuel Faure (BIOIMAGING, 2019)

Ensemble Of Neural Networks For High Endothelial Venules Detection In Meca-79 Immunohistochemistry Images. - Arnaud Abreu; Camille Franchet; François-Xavier Frenois; Pierre Brousset; Jean-Philippe Girard; Patrice Denéfle; Benoît Naegel; Cédric Wemmert (ISBI, 2019)

A Study on the Impact of Class Distribution on Deep Learning - The Case of Histological Images and Cancer Detection - Extended Abstract. - Ismat Ara Reshma; Josiane Mothe; Sylvain Cussat-Blanc; Hervé Luga; Camille Franchet; Margot Gaspard; Pierre Brousset; Radu Tudor Ionescu (CIRCLE, 2022)

Finding a Suitable Class Distribution for Building Histological Images Datasets Used in Deep Model Training - The Case of Cancer Detection. - Ismat Ara Reshma; Camille Franchet; Margot Gaspard; Radu Tudor Ionescu; Josiane Mothe; Sylvain Cussat-Blanc; Hervé Luga; Pierre Brousset (J. Digit. Imaging, 2022)

Bias reduction using combined stain normalization and augmentation for AI-based classification of histological images. - Camille Franchet; Robin Schwob; Guillaume Bataillon; Charlotte Syrykh; Sarah Péricart; François-Xavier Frenois; Frédérique Penault-Llorca; Magali Lacroix-Triki; Laurent Arnould; Jérôme Lemonnier; Jean-Marc Alliot; Thomas Filleron; et al. (Comput. Biol. Medicine, 2024)

Réduction du biais lié à la coloration des coupes histologiques de cancer du sein pour le développement d'outils de classification par intelligence artificielle. (Reduction of color-induced bias for artificial intelligence-based classification of breast cancer histological images). - Camille Franchet (2024)

Evolved and Transparent Pipelines for Biomedical Image Classification. - Camilo De La Torre; Giorgia Nadizar; Yuri Lavinas; Robin Schwob; Camille Franchet; Hervé Luga; Dennis Wilson; Sylvain Cussat-Blanc (EuroGP, 2025)