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Automated crater detection with human level performance
DOI: 10.1016/j.cageo.2020.104645
Bibcode: 2021CG....14704645L
Lee, Christopher; Hogan, James
Crater cataloging is an important yet time-consuming part of geological mapping. We present an automated Crater Detection Algorithm (CDA) that is competitive with expert-human researchers and hundreds of times faster.
The CDA uses multiple neural networks to process digital terrain model and thermal infra-red imagery to identify and locate cr…
2021
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Computers and Geosciences
MEx
11