Roberto Interdonato
@interdonatos.bsky.social
Senior Researcher @ CIRAD, UMR TETIS (Montpellier) and INRIA team-project EVERGREEN (Earth observation and machine learning for agro-environmental challenges). AI/complex networks/food security/agriculture. But also good food/music/literature/photography.
Reposted by Roberto Interdonato
We show that our multi-sensor approach is more robust in average than recent methods from the EO literature in three classification tasks, namely cropland classification, crop-type classification, and tree-species classification.
@interdonatos.bsky.social
@interdonatos.bsky.social
May 13, 2025 at 11:37 AM
We show that our multi-sensor approach is more robust in average than recent methods from the EO literature in three classification tasks, namely cropland classification, crop-type classification, and tree-species classification.
@interdonatos.bsky.social
@interdonatos.bsky.social