4 papers
Self-Supervised Representation Learning: From Spectral Foundation Models to Auroral Emission Spectra
Matthieu Le Lain, Gaël Cessateur, Sébastien Lefèvre
Auroral spectrographs such as the Auroral Spectrograph In Skibotn (ASIS) record hundreds of thousands of emission spectra, but only a few hundred can be labelled by an expert. To e…
EoS-FM: Can an Ensemble of Specialist Models act as a Generalist Feature Extractor?
Pierre Adorni, Minh-Tan Pham, Stéphane May +1
Recent advances in foundation models have shown great promise in domains such as natural language processing and computer vision, and similar efforts are now emerging in the Earth…
Towards Efficient Benchmarking of Foundation Models in Remote Sensing: A Capabilities Encoding Approach
Pierre Adorni, Minh-Tan Pham, Stéphane May +1
Foundation models constitute a significant advancement in computer vision: after a single, albeit costly, training phase, they can address a wide array of tasks. In the field of Ea…
Mapping earth mounds from space
Baki Uzun, Shivam Pande, Gwendal Cachin-Bernard +4
Regular patterns of vegetation are considered widespread landscapes, although their global extent has never been estimated. Among them, spotted landscapes are of particular interes…