22 citations · 36 across the 6 of their papers we have counts for
4 papers · 1 filter
Multimodal-Multiresolution Foundation Model for Lunar Remote Sensing
Paolo Fraccaro, Gabby Nyirjesy, Daniela Szwarcman +19
We present a multimodal foundation model for lunar remote sensing, pretrained from scratch on SomBench, a geographically partitioned corpus of nearly two million co-registered tile…
SomBench: Benchmark Dataset for Advancing Machine Learning in Lunar Science
Himanshu Patil, Gabby Nyirjesy, Rachel A. Slank +19
Lunar orbital missions, such as Lunar Reconnaissance Orbiter, Kaguya/SELENE, Gravity Recovery and Interior Laboratory, and Lunar Prospector, among others, provide rich multi-instru…
TerraTorch: The Geospatial Foundation Models Toolkit
Carlos Gomes, Benedikt Blumenstiel, Joao Lucas de Sousa Almeida +7
TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrate…
Prithvi-EO-2.0: A Versatile Multi-Temporal Foundation Model for Earth Observation Applications
Daniela Szwarcman, Sujit Roy, Paolo Fraccaro +33
This paper presents Prithvi-EO-2.0, a new geospatial foundation model that offers significant improvements over its predecessor, Prithvi-EO-1.0. Trained on 4.2 million global time…