Remote Sensing Intelligent Interpretation for Mine Geological Environment

Lieferzeit: Lieferbar innerhalb 14 Tagen

181,89 

From Land Use and Land Cover Perspective

ISBN: 9811937389
ISBN 13: 9789811937385
Autor: Chen, Weitao/Li, Xianju/Wang, Lizhe
Verlag: Springer Verlag GmbH
Umfang: xii, 246 S., 21 s/w Illustr., 89 farbige Illustr., 246 p. 110 illus., 89 illus. in color.
Erscheinungsdatum: 19.08.2022
Auflage: 1/2023
Produktform: Gebunden/Hardback
Einband: Gebunden

Combines interdisciplinary expertise RS and AI to improve the automatic interpretation of mine geological environmentConstructs a systematic mine remote sensing dataset focusing on the multi-level taskIntroduces deep learning technology for mine-targeted remote sensing detection and scene classification of mine

Artikelnummer: 5669600 Kategorie:

Beschreibung

Autorenporträt

Dr. Weitao Chen (Member, IEEE) is a professor at the School of Computer Science, China Univ. of Geosciences (CUG). He received B.E. from Jiaozuo Institute of Technology in 2003, M.E from in 2006 and Doctor from China Univ. of Geosciences in 2012. He has published more than 30 peer-reviewed technical papers in international journals. His main research interests include machine learning and remote sensing of environment. Prof. Chen is a member of IEEE and served as a reviewer of several international journals. He was awarded the land and resources science and Technology Progress Award (second prize in 2019), and the science and technology Award (second prize) of China command and control society (second prize in 2020). He was awarded "cradle plan" talent project of China University of Geosciences and the "Chenguang plan" talent project of Youth Science and technology in Wuhan, Hubei Province Dr. Xianju Li received the B.S., M.S., and Ph.D. degrees from China University of Geoscience, Wuhan, China, in 2009, 2012, and 2016, respectively. Since 2016, he has been an associate professor in the School of Computer Science, China University of Geosciences. He has published more than 10 peer-reviewed technical papers in international journals. His main research fields include remote sensing image processing and analysis, computer vision, and machine learning. He was awarded the land and resources science and Technology Progress Award (second prize in 2019).

Herstellerkennzeichnung:


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E-Mail: juergen.hartmann@springer.com

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