A Deep Learning Approach to Species Distribution Modelling. - Christophe Botella; Alexis Joly; Pierre Bonnet; Pascal Monestiez; François Munoz (Multimedia Tools and Applications for Environmental & Biodiversity Informatics, 2018)

Overview of GeoLifeCLEF 2018: Location-based Species Recommendation. - Christophe Botella; Pierre Bonnet; François Munoz; Pascal Monestiez; Alexis Joly (CLEF (Working Notes), 2018)

Participation of LIRMM / Inria to the GeoLifeCLEF 2020 Challenge. - Benjamin Deneu; Maximilien Servajean; Pierre Bonnet; François Munoz; Alexis Joly (CLEF (Working Notes), 2020)

How Do Deep Convolutional SDM Trained on Satellite Images Unravel Vegetation Ecology? - Benjamin Deneu; Alexis Joly; Pierre Bonnet; Maximilien Servajean; François Munoz (ICPR Workshops (6), 2020)

Convolutional neural networks improve species distribution modelling by capturing the spatial structure of the environment. - Benjamin Deneu; Maximilien Servajean; Pierre Bonnet; Christophe Botella; François Munoz; Alexis Joly (PLoS Comput. Biol., 2021)

AI-based Mapping of the Conservation Status of Orchid Assemblages at Global Scale. - Joaquim Estopinan; Maximilien Servajean; Pierre Bonnet; Alexis Joly; François Munoz (CoRR, 2024)

Modelling Species Distributions with Deep Learning to Predict Plant Extinction Risk and Assess Climate Change Impacts. - Joaquim Estopinan; Pierre Bonnet; Maximilien Servajean; François Munoz; Alexis Joly (CoRR, 2024)

Mapping global orchid assemblages with deep learning provides novel conservation insights. - Joaquim Estopinan; Maximilien Servajean; Pierre Bonnet; Alexis Joly; François Munoz (Ecol. Informatics, 2024)