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DSA-Net: A novel deeply supervised attention-guided network for building change detection in high-resolution remote sensing images

  • Published:2021-12 Issue: Volume:105 Page:102591
  • ISSN:0303-2434
  • Container-title:International Journal of Applied Earth Observation and Geoinformation
  • language:en
  • Short-container-title:International Journal of Applied Earth Observation and Geoinformation

Author:

Ding Qing,Shao Zhenfeng,Huang Xiao,Altan Orhan

Publisher

Elsevier BV

Subject

Management, Monitoring, Policy and Law,Computers in Earth Sciences,Earth-Surface Processes,Global and Planetary Change

Cited by 58 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A multi-view ensemble model based on semi-supervised feature learning for small sample classification of PolSAR images;International Journal of Remote Sensing;2024-01-28

2. A Lightweight Change Detection Network Based on Feature Interleaved Fusion and Bistage Decoding;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

3. FDFF-Net: A Full-Scale Difference Feature Fusion Network for Change Detection in High-Resolution Remote Sensing Images;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

4. SASiamNet: Self-Adaptive Siamese Network for Change Detection of Remote Sensing Image;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

5. Land Cover Change Detection Based on Vector Polygons and Deep Learning With High-Resolution Remote Sensing Images;IEEE Transactions on Geoscience and Remote Sensing;2024
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