Improved DeepLabv3+ Based Flood Water Body Extraction Model for SAR Imagery-Reference-Cited by-同舟云学术

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Improved DeepLabv3+ Based Flood Water Body Extraction Model for SAR Imagery

Published:2024-07-07 Issue: Volume:0 Page:1196-1199
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Qin Chen-Hao¹,Li Wei-Bin¹,Zhang Tian-Yi¹,Ji Wen-Bo¹,Feng Xi-Hui²,Ren Yi³

Affiliation:

1. Xidian University,School of Artificial Intelligence,Xi’an,China,710071

2. Ministry of Natural Resources,Key Lab. of Coal Resources Exploration and Comprehensive Utilization,Xi’an,China,710021

3. Xidian University,Lab. of AI, Hangzhou Institute of Technology,Hangzhou,China,311231

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10640606.pdf?arnumber=10640606

Reference12 articles.

1. Research on SAR water body information extraction based on convolutional neural network;Wu;Hefei University of Technology,2020

2. SAR image analysis techniques for flood area mapping - literature survey

3. Classification and Segmentation of Satellite Orthoimagery Using Convolutional Neural Networks

4. Multi-source remote sensing image flood disaster information extraction and change analysis based on improved U-Net network;Che;Bulletin of Surveying and Mapping,2022

5. A New Lightweight Convolutional Neural Network for Multi-Scale Land Surface Water Extraction from GaoFen-1D Satellite Images

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