火星Mawrth Vallis，使用NOAH-H深度学习地形分类系统进行分类

IF 1.9 4区地球科学 Q2 GEOGRAPHY Journal of Maps Pub Date : 2023-11-28 DOI:10.1080/17445647.2023.2285480

Alexander M. Barrett, Peter Fawdon, Elena A. Favaro, Matthew R. Balme, Jack Wright, Mark J. Woods, Spyros Karachalios, Eleni Bohacek, Levin Gerdes, Elliot Sefton-Nash, Luc Joudrier

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摘要

利用深度学习(DL)地形分类系统“新奇与异常猎人- HiRISE”(NOAH-H)生成了火星Mawrth Vallis的地形图。有了它，我们数字化了范围和…

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Mawrth Vallis, Mars, classified using the NOAH-H deep-learning terrain classification system

A deep learning (DL) terrain classification system, the Novelty and Anomaly Hunter – HiRISE (NOAH-H) was used to produce a terrain map of Mawrth Vallis, Mars. With it, we digitised the extent and d...

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来源期刊

Journal of Maps 地学-自然地理

CiteScore

4.30

自引率

9.10%

发文量

审稿时长

6-12 weeks

期刊介绍： The Journal of Maps is a peer-reviewed, inter-disciplinary, online journal that aims to provide a forum for researchers to publish maps and spatial diagrams.