Automated crater detection algorithms from a machine learning perspective in the convolutional neural network era
Autor: | Nicholas Guttenberg, Takehisa Yairi, D. M. DeLatte, Sarah T. Crites |
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Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
Atmospheric Science
010504 meteorology & atmospheric sciences Computer science Feature extraction Aerospace Engineering Mars Machine learning computer.software_genre 01 natural sciences Convolutional neural network Edge detection Field (computer science) Automation Impact crater 0103 physical sciences 010303 astronomy & astrophysics 0105 earth and related environmental sciences business.industry Process (computing) Astronomy and Astrophysics Crater counting Geophysics Space and Planetary Science General Earth and Planetary Sciences Crater detection Convolutional neural networks Artificial intelligence business Algorithm computer |
Zdroj: | Advances in Space Resarch. 64(8):1615-1628 |
ISSN: | 0273-1177 |
Popis: | Accepted: 2019-07-11 資料番号: SA1190111000 |
Databáze: | OpenAIRE |
Externí odkaz: |