Research on Recognition Methods of Elm Sparse Forest based on Object-based Image Analysis and Deep Learning

Ang CHEN; Xiuchun YANG; Bin XU; Yunxiang JIN; Wenbo ZHANG; Jian GUO; Xiaoyu XING; Dong YANG

doi:10.12082/dqxxkx.2019.190598

Journals >Journal of Geo-information Science >Volume 22 >Issue 9 >Page 1897 > Article

Journal of Geo-information Science
Vol. 22, Issue 9, 1897 (2020)

Research on Recognition Methods of Elm Sparse Forest based on Object-based Image Analysis and Deep Learning

Ang CHEN¹, Xiuchun YANG^1、2、*, Bin XU^1、2, Yunxiang JIN¹, Wenbo ZHANG¹, Jian GUO¹, Xiaoyu XING¹, and Dong YANG¹

Author Affiliations

¹Key Laboratory of Agri-informatics, Ministry of Agriculture/Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

²College of Grassland Science, Beijing Forestry University, Beijing 100083, China

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DOI: 10.12082/dqxxkx.2019.190598 Cite this Article

Ang CHEN, Xiuchun YANG, Bin XU, Yunxiang JIN, Wenbo ZHANG, Jian GUO, Xiaoyu XING, Dong YANG. Research on Recognition Methods of Elm Sparse Forest based on Object-based Image Analysis and Deep Learning[J]. Journal of Geo-information Science, 2020, 22(9): 1897 Copy Citation Text

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