4 citations · 4 across the 3 of their papers we have counts for
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astro-ph.EP2026
A Machine Learning Based Search for Lunar Anomalies
Cameron Kelahan, Daniel Angerhausen, Adam Lesnikowski +1
The Lunar Reconnaissance Orbiter (LRO) has been collecting high-resolution images (at around 0.5-2 meters per pixel linearly with its Narrow Angle Camera) of the Moon since 2009, a…
astro-ph.EP2026
Machine Learning as a Transformative Tool for (Exo-)Planetary Science
J. Davoult, V. T. Bickel, C. Haslebacher +11
The exploration of planetary bodies in our Solar system and beyond relies on the processing and interpretation of large, spatio-temporally inconsistent, and heterogeneous datasets.…