Mapping of land cover in semi-arid regions based on a multi-gate semi-supervised learning method – a case study of Zhangbei, China-Reference-Cited by-同舟云学术

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Mapping of land cover in semi-arid regions based on a multi-gate semi-supervised learning method – a case study of Zhangbei, China

Published:2021-12-19 Issue:2 Volume:13 Page:207-217
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Chen Boan¹^ORCID,Feng Quanlong¹,Niu Bowen¹,Yang Jianyu¹,Gao Bingbo¹,Liu Jiantao²,Wang Weitao³,Li Chenxi¹,Zhao Yuanyuan¹,Guo Hao¹,Ma Qin³

Affiliation:

1. College of Land Science and Technology, China Agricultural University, Beijing, China

2. School of Surveying and Geo-Informatics, Shandong Jianzhu University, Jinan, China

3. College of Information and Electrical Engineering, China Agricultural University, Beijing, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2021.2012292

Reference13 articles.

1. Semi-supervised Deep Learning for Fully Convolutional Networks

2. Integrating Multitemporal Sentinel-1/2 Data for Coastal Land Cover Classification Using a Multibranch Convolutional Neural Network: A Case of the Yellow River Delta

3. The Role of Lithology

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2. Comparative Analysis of Multispectral and Hyperspectral Imagery for Mapping Sugarcane Varieties;PFG – Journal of Photogrammetry, Remote Sensing and Geoinformation Science;2023-09-06

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