High-spatial-resolution remote sensing image segmentation using adaptive watershed-driven joint MDEDNet

Zenan Yanga School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, ChinaView further author information

Haipeng Niua School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, China;b Research Centre of Arable Land Protection and Urban-rural High-quality Development of Yellow River Basin, Jiaozuo, Henan, ChinaCorrespondence[email protected]
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Liang Huangc Faculty of Land Resources Engineering, Kunming University of Science and Technology, Kunming, Yunnan, China;d Surveying and Mapping Geo-Informatics Technology Research Center on Plateau Mountains of Yunnan Higher Education, Kunming, Yunnan, ChinaView further author information

Dongyang Xiaoa School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, ChinaView further author information

Xiaoxuan Wange Key Laboratory of Spatio-temporal Information and Ecological Restoration of Mines of Natural Resources of the People's Republic of China, Henan Polytechnic University, Jiaozuo, Henan, ChinaView further author information

Jinke Suna School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo, Henan, ChinaView further author information

High-spatial-resolution remote sensing image segmentation using adaptive watershed-driven joint MDEDNet

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High-spatial-resolution remote sensing image segmentation using adaptive watershed-driven joint MDEDNet

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