EDWNet: A Novel Encoder–Decoder Architecture Network for Water Body Extraction from Optical Images

Automated water body (WB) extraction is one of the hot research topics in the field of remote sensing image processing. To address the challenges of over-extraction and incomplete extraction in complex water scenes, we propose an encoder–decoder architecture semantic segmentation network for high-pr...

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Veröffentlicht in:	Remote sensing (Basel, Switzerland) Jg. 16; H. 22; S. 4275
Hauptverfasser:	Zhang, Tianyi, Ji, Wenbo, Li, Weibin, Qin, Chenhao, Wang, Tianhao, Ren, Yi, Fang, Yuan, Han, Zhixiong, Jiao, Licheng
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Basel MDPI AG 01.11.2024
Schlagworte:	Algorithms Analysis Artificial intelligence China Classification Climate change Coders Computer vision Dams Deep learning Diffusion layers Earth resources technology satellites EDWNet Image enhancement Image processing Image segmentation Information processing Landsat Modules Neural networks Remote sensing River basins Satellite imagery Semantic segmentation Surface water Water bodies water body Weihe river basin China Weihe River Yellow River
ISSN:	2072-4292, 2072-4292
Online-Zugang:	Volltext
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