CGMMA: CNN-GNN Multiscale Mixed Attention Network for Remote Sensing Image Change Detection-Reference-Cited by-同舟云学术

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CGMMA: CNN-GNN Multiscale Mixed Attention Network for Remote Sensing Image Change Detection

Published:2024 Issue: Volume:17 Page:7089-7103
ISSN:1939-1404
Container-title:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
language:
Short-container-title:IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

Author:

Zhang Yan¹^ORCID,Song Xinyang¹^ORCID,Hua Zhen²^ORCID,Li Jinjiang¹^ORCID

Affiliation:

1. School of Information and electronic engineering, Shandong Technology and Business University, Institute of Network Technology (ICT), Yantai, China

2. School of Computer Science and Technology, Shandong Technology and Business University, Yantai, China

Funder

National Natural Science Foundation of China

Shandong Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/4609443/10330207/10414003.pdf?arnumber=10414003

Reference52 articles.

1. Review Article Digital change detection techniques using remotely-sensed data

2. Generating high-accuracy urban distribution map for short-term change monitoring based on convolutional neural network by utilizing SAR imagery

4. Change Detection of Deforestation in the Brazilian Amazon Using Landsat Data and Convolutional Neural Networks

5. Land cover characterization and change detection for environmental monitoring of pan-Europe

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