3 papers
cs.CV2022
Improving Contrastive Learning on Visually Homogeneous Mars Rover Images
Isaac Ronald Ward, Charles Moore, Kai Pak +2
Contrastive learning has recently demonstrated superior performance to supervised learning, despite requiring no training labels. We explore how contrastive learning can be applied…
cs.CV2022
Mixed-domain Training Improves Multi-Mission Terrain Segmentation
Grace Vincent, Alice Yepremyan, Jingdao Chen +1
Planetary rover missions must utilize machine learning-based perception to continue extra-terrestrial exploration with little to no human presence. Martian terrain segmentation has…
cs.CV2022
Mars Terrain Segmentation with Less Labels
Edwin Goh, Jingdao Chen, Brian Wilson
Planetary rover systems need to perform terrain segmentation to identify drivable areas as well as identify specific types of soil for sample collection. The latest Martian terrain…