most citedAutomatic characterization of boulders on planetary surfaces from high-resolution satellite images

19 citations · 47 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20246 cited

Multi-Region Transfer Learning for Segmentation of Crop Field Boundaries in Satellite Images with Limited Labels

Hannah Kerner, Saketh Sundar, Mathan Satish

The goal of field boundary delineation is to predict the polygonal boundaries and interiors of individual crop fields in overhead remotely sensed images (e.g., from satellites or d…

cs.LG202416 cited

Mission Critical -- Satellite Data is a Distinct Modality in Machine Learning

Esther Rolf, Konstantin Klemmer, Caleb Robinson +1

Satellite data has the potential to inspire a seismic shift for machine learning -- one in which we rethink existing practices designed for traditional data modalities. As machine…

astro-ph.EP202419 cited

Automatic characterization of boulders on planetary surfaces from high-resolution satellite images

Nils C. Prieur, Brian Amaro, Emiliano Gonzalez +7

Boulders form from a variety of geological processes, which their size, shape, and orientation may help us better understand. Furthermore, they represent potential hazards to space…

cs.CV2023

ConeQuest: A Benchmark for Cone Segmentation on Mars

Mirali Purohit, Jacob Adler, Hannah Kerner

Over the years, space scientists have collected terabytes of Mars data from satellites and rovers. One important set of features identified in Mars orbital images is pitted cones,…

cs.AI20236 cited

Reflections from the Workshop on AI-Assisted Decision Making for Conservation

Lily Xu, Esther Rolf, Sara Beery +21

In this white paper, we synthesize key points made during presentations and discussions from the AI-Assisted Decision Making for Conservation workshop, hosted by the Center for Res…