A Lightweight Dual-Branch Network for Building Change Detection in Remote Sensing Images Integrating Cross-Scale Coupling and Boundary Constraint-Reference-Cited by-同舟云学术

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A Lightweight Dual-Branch Network for Building Change Detection in Remote Sensing Images Integrating Cross-Scale Coupling and Boundary Constraint

Published:2024 Issue: Volume:62 Page:1-15
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Dai Yanshuai¹^ORCID,Shen Li¹^ORCID,Wang Yong²,Liu Shichuan¹^ORCID,Li Zhilin¹

Affiliation:

1. State-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, China

2. Key Laboratory of Investigation, Monitoring, Protection and Utilization for Cultivated Land Resources, MNR, Sichuan Institute of Land Science and Technology (Sichuan Center of Satellite Application Technology), Chengdu, China

Funder

National Natural Science Foundation of China

Financial Fund of Sichuan Institute of Geological Survey

Financial Fund of Sichuan Provincial Department of Natural Resources

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10633742.pdf?arnumber=10633742

Reference38 articles.

1. Building Change Detection From Multitemporal High-Resolution Remotely Sensed Images Based on a Morphological Building Index

2. Change detection using deep learning approach with object-based image analysis

3. Fine-Grained Building Change Detection From Very High-Spatial-Resolution Remote Sensing Images Based on Deep Multitask Learning

4. Deep Residual Learning for Image Recognition

5. Going deeper with convolutions

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