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Cartography and Geographic Information Science Volume 49, 2022 - Issue 4
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Articles

Polyline simplification based on the artificial neural network with constraints of generalization knowledge

Jiawei DuPLA Strategic Support Force, Information Engineering University, Zhengzhou, Henan, ChinaView further author information
,
Fang WuPLA Strategic Support Force, Information Engineering University, Zhengzhou, Henan, ChinaCorrespondence[email protected]
View further author information
,
Jichong YinPLA Strategic Support Force, Information Engineering University, Zhengzhou, Henan, ChinaView further author information
,
Chengyi LiuPLA Strategic Support Force, Information Engineering University, Zhengzhou, Henan, ChinaView further author information
&
Xianyong GongPLA Strategic Support Force, Information Engineering University, Zhengzhou, Henan, ChinaORCID Iconhttps://orcid.org/0000-0002-6184-1300View further author information
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Pages 313-337 | Received 04 Dec 2020, Accepted 30 Nov 2021, Published online: 17 Jan 2022

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Read on this site (3)

Xiongfeng Yan & Min Yang. (2023) A deep learning approach for polyline and building simplification based on graph autoencoder with flexible constraints. Cartography and Geographic Information Science 0:0, pages 1-18.
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Tianyuan Xiao, Tinghua Ai, Huafei Yu, Min Yang & Pengcheng Liu. (2023) A point selection method in map generalization using graph convolutional network model. Cartography and Geographic Information Science 0:0, pages 1-21.
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Cheng Fu, Zhiyong Zhou, Yu Feng & Robert Weibel. Keeping walls straight: data model and training set size matter for deep learning in building generalization. Cartography and Geographic Information Science 0:0, pages 1-16.
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Articles from other publishers (1)

Cheng-Hong Yang, Guan-Cheng Lin, Chih-Hsien Wu, Yen-Hsien Liu, Yi-Chuan Wang & Kuo-Chang Chen. (2022) Deep Learning for Vessel Trajectory Prediction Using Clustered AIS Data. Mathematics 10:16, pages 2936.
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