Automatic extraction of surface water based on lightweight convolutional neural network-Reference-Cited by-同舟云学术

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Automatic extraction of surface water based on lightweight convolutional neural network

Published:2023-05 Issue: Volume:256 Page:114843
ISSN:0147-6513
Container-title:Ecotoxicology and Environmental Safety
language:en
Short-container-title:Ecotoxicology and Environmental Safety

Author:

Wan Jikang,Yong Bin

Funder

Hohai University

National Key Research and Development Program of China

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Health, Toxicology and Mutagenesis,Public Health, Environmental and Occupational Health,Pollution,General Medicine

Reference48 articles.

1. Global extent of rivers and streams;Allen;Science,2018

2. Automatic boundary extraction of inland water bodies using LiDAR data;Canaz;Ocean Coast. Manag.,2015

3. Global land surface water mapping and analysis at 30 m spatial resolution for years 2000 and 2010;Cao;Multitemporal Remote Sens.,2016

4. Encoder-decoder with atrous separable convolution for semantic image segmentation;Chen;Comput. Vis. – ECCV,2018

5. Extraction of urban water bodies from high-resolution remote-sensing imagery using deep learning;Chen;Water,2018

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1. Recognition of small water bodies under complex terrain based on SAR and optical image fusion algorithm;Science of The Total Environment;2024-10

2. Land Use Recognition by Applying Fuzzy Logic and Object-Based Classification to Very High Resolution Satellite Images;Remote Sensing;2024-06-21

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