Seeing the forest and the trees: How hyperspatial drone imagery is revolutionizing tropical canopy studies (ecological focus)
4 novembre 2025 @ 11 h 00 min – 12 h 00 min –
CIRAD Campus Lavalette – Amphi Jacques Alliot – Bâtiment 4
Machine Learning in Montpellier, Theory & Practice – Étienne Laliberté (Université de Montréal)
Dans le cadre des échanges Inria–IVADO, nous aurons le plaisir d’accueillir à Montpellier du 3 au 14 novembre 2025, Étienne Laliberté, professeur titulaire au Département des sciences biologiques de l’Université de Montréal et membre académique associé au Mila (Institut québécois d’intelligence artificielle).
IA et Experts
IA : Introduction au Deep Learning
4 novembre 2025 @ 14 h 00 min – 16 h 30 min –
Campus Triolet, Campus Triolet, Bat 36, SC36.06
Gino Frazzoli – Institut de Science des Données de Montpellier
Plongez au cœur de l’intelligence artificielle avec les bases du Deep Learning. Une première partie vous apportera notions-clés et terminologie nécessaires pour comprendre et suivre le cas pratique proposé : la classification de deux espèces.
Deep Learning, IA, Classification
Seeing the forest and the trees: How hyperspatial drone imagery is revolutionizing tropical canopy studies (ecological focus)
4 novembre 2025 @ 14 h 00 min –
Amphi Jacques Alliot, Building 4, CIRAD Campus Lavalette
Machine Learning in Montpellier, Theory & Practice – Étienne Laliberté (Univ. Montréal / MILA)
Tropical forests hold the majority of terrestrial plant carbon and biodiversity, but they are being altered with climate change. However, we do not know how the vast majority of tropical tree species are responding to climate change and other stressors because traditional field-based approaches cannot collect sufficiently large sample sizes for most species. As part of the winning team of the XPRIZE Rainforest competition, we have developed an AI solution using drone imagery that can greatly accelerate the mapping of tropical trees. The drone hardware needed is affordable and readily accessible to researchers and conservation agencies. In this talk, I will present this technology, which I will argue has the potential to revolutionize tropical forest science, conservation, and restoration. I will talk about the opportunities, as well as some challenges that need to be addressed to unlock the potential of this technology for tropical canopy studies.
Machine Learning in Montpellier, Theory & Practice