中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Classification of High-Resolution Remote Sensing Images in the Feilaixia Reservoir Based on a Fully Convolutional Network

文献类型:期刊论文

作者Wu, Pinghao2,3,4; Zhong, Kaiwen1,2; Hu, Hongda2,5; Xu, Jianhui2,5; Wang, Yunpeng3; Zhao, Yi2,3,4
刊名IEEE ACCESS
出版日期2020
卷号8页码:161752-161764
ISSN号2169-3536
DOI10.1109/ACCESS.2020.3021071
WOS研究方向Computer Science ; Engineering ; Telecommunications
语种英语
WOS记录号WOS:000570086900001
源URL[http://ir.gig.ac.cn/handle/344008/57734]  
专题中国科学院广州地球化学研究所
通讯作者Zhong, Kaiwen
作者单位1.Guangdong Nat Resources Sci & Technol Collaborat, Guangzhou 510070, Peoples R China
2.Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Key Lab Guangdong Utilizat Remote Sensing & Geog, Guangzhou 510070, Peoples R China
3.Chinese Acad Sci, Guangzhou Inst Geochem, Guangzhou 510640, Peoples R China
4.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China
5.Southern Marine Sci & Engn Guangdong Lab Guangzho, Guangzhou 511458, Peoples R China
推荐引用方式
GB/T 7714
Wu, Pinghao,Zhong, Kaiwen,Hu, Hongda,et al. Classification of High-Resolution Remote Sensing Images in the Feilaixia Reservoir Based on a Fully Convolutional Network[J]. IEEE ACCESS,2020,8:161752-161764.
APA Wu, Pinghao,Zhong, Kaiwen,Hu, Hongda,Xu, Jianhui,Wang, Yunpeng,&Zhao, Yi.(2020).Classification of High-Resolution Remote Sensing Images in the Feilaixia Reservoir Based on a Fully Convolutional Network.IEEE ACCESS,8,161752-161764.
MLA Wu, Pinghao,et al."Classification of High-Resolution Remote Sensing Images in the Feilaixia Reservoir Based on a Fully Convolutional Network".IEEE ACCESS 8(2020):161752-161764.

入库方式: OAI收割

来源:广州地球化学研究所

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