1 citations · 1 across the 1 of their papers we have counts for
2 papers
cs.CV2024
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…
cs.CV2024★ 1 cited
Comparing Deep Learning Models for Rice Mapping in Bhutan Using High Resolution Satellite Imagery
Biplov Bhandari, Timothy Mayer
The Bhutanese government is increasing its utilization of technological approaches such as including Remote Sensing-based knowledge in their decision-making process. This study foc…