Empirical analysis of the residual information needed for image classification. - Rebecca Leygonie; Guillaume Vimont (IEEE BigData, 2021)

An a contrario approach for plant disease detection. - Rebecca Leygonie; Sylvain Lobry; Laurent Wendling (BMVC Workshop, 2023)

Transforming Multidimensional Data into Images to Overcome the Curse of Dimensionality. - Rebecca Leygonie; Sylvain Lobry; Guillaume Vimont; Laurent Wendling (ICIP, 2023)

Deep learning for classification of noisy QR codes. - Rebecca Leygonie; Sylvain Lobry; Laurent Wendling (CoRR, 2023)

Can we detect plant diseases without prior knowledge of their existence? - Rebecca Leygonie; Sylvain Lobry; Laurent Wendling (Int. J. Appl. Earth Obs. Geoinformation, 2024)

Impact de la représentation de l'information sur les performances et la validation des modèles d'apprentissage profond. (Impact of information representation on the performance and validation of deep learning models). - Rebecca Leygonie (2024)

Représentation des poids d'auto-attention sous forme de graphe pour l'évaluation des Transformers. - Rebecca Leygonie; Sylvain Lobry; Laurent Wendling (EGC, 2025)

Evaluating Transformers Learning by Representing Self-Attention Weights as a Graph. - Rebecca Leygonie; Sylvain Lobry; Laurent Wendling (VISIGRAPP (1): GRAPP, HUCAPP, IVAPP, 2025)