Water index and Swin Transformer Ensemble (WISTE) for water body extraction from multispectral remote sensing images

Water index and Swin Transformer Ensemble (WISTE) for water body extraction from multispectral remote sensing images

Automatic surface water body mapping using remote sensing technology is greatly meaningful for studying inland water dynamics at regional to global scales. Convolutional neural networks (CNN) have become an efficient semantic segmentation technique for the interpretation of remote sensing images. Ho...

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Bibliographic Details
Main Authors: Donghui Ma, Liguang Jiang, Jie Li, Yun Shi
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:GIScience & Remote Sensing
Subjects:
deep learning
water body extraction
swin transformer
water index
dual-encoder
Online Access:http://dx.doi.org/10.1080/15481603.2023.2251704

Internet

http://dx.doi.org/10.1080/15481603.2023.2251704

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