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- Publisher Website: 10.1109/TGRS.2024.3386918
- Scopus: eid_2-s2.0-85190791941
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Article: CAS-Net: Comparison-Based Attention Siamese Network for Change Detection With an Open High-Resolution UAV Image Dataset
Title | CAS-Net: Comparison-Based Attention Siamese Network for Change Detection With an Open High-Resolution UAV Image Dataset |
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Authors | |
Keywords | Change detection (CD) dataset Siamese network unmanned aerial vehicle (UAV) |
Issue Date | 18-Apr-2024 |
Publisher | IEEE |
Citation | IEEE Transactions on Geoscience and Remote Sensing, 2024, v. 62, p. 1-17 How to Cite? |
Abstract | Change detection (CD) is a process of extracting changes on the Earth s surface from bitemporal images. Current CD methods that use high-resolution remote sensing images require extensive computational resources and are vulnerable to the presence of irrelevant noises in the images. In addressing these challenges, a comparison-based attention Siamese network (CAS-Net) is proposed. The network utilizes contrastive attention modules (CAMs) for feature fusion and employs a classifier to determine similarities and differences of bitemporal image patches. It simplifies pixel-level CDs by comparing image patches. As such, the influences of image background noises on change predictions are reduced. Along with the CAS-Net, an unmanned aerial vehicle (UAV) similarity detection (UAV-SD) dataset is built using high-resolution remote sensing images. This dataset, serving as a benchmark for CD, comprises 10 000 pairs of UAV images with a size of 256 × 256. Experiments of the CAS-Net on the UAV-SD dataset demonstrate that the CAS-Net is superior to other baseline CD networks. The CAS-Net detection accuracy is 93.1% on the UAV-SD dataset. The code and the dataset can be found at https://github.com/WenbaLi/CAS-Net . |
Persistent Identifier | http://hdl.handle.net/10722/348126 |
ISSN | 2023 Impact Factor: 7.5 2023 SCImago Journal Rankings: 2.403 |
DC Field | Value | Language |
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dc.contributor.author | Zhai, Yikui | - |
dc.contributor.author | Li, Wenba | - |
dc.contributor.author | Xian, Tingfeng | - |
dc.contributor.author | Jia, Xudong | - |
dc.contributor.author | Zhang, Hongsheng | - |
dc.contributor.author | Tan, Zijun | - |
dc.contributor.author | Zhou, Jianhong | - |
dc.contributor.author | Zeng, Junying | - |
dc.contributor.author | Philip Chen, C L | - |
dc.date.accessioned | 2024-10-05T00:30:41Z | - |
dc.date.available | 2024-10-05T00:30:41Z | - |
dc.date.issued | 2024-04-18 | - |
dc.identifier.citation | IEEE Transactions on Geoscience and Remote Sensing, 2024, v. 62, p. 1-17 | - |
dc.identifier.issn | 0196-2892 | - |
dc.identifier.uri | http://hdl.handle.net/10722/348126 | - |
dc.description.abstract | <p>Change detection (CD) is a process of extracting changes on the Earth s surface from bitemporal images. Current CD methods that use high-resolution remote sensing images require extensive computational resources and are vulnerable to the presence of irrelevant noises in the images. In addressing these challenges, a comparison-based attention Siamese network (CAS-Net) is proposed. The network utilizes contrastive attention modules (CAMs) for feature fusion and employs a classifier to determine similarities and differences of bitemporal image patches. It simplifies pixel-level CDs by comparing image patches. As such, the influences of image background noises on change predictions are reduced. Along with the CAS-Net, an unmanned aerial vehicle (UAV) similarity detection (UAV-SD) dataset is built using high-resolution remote sensing images. This dataset, serving as a benchmark for CD, comprises 10 000 pairs of UAV images with a size of 256 × 256. Experiments of the CAS-Net on the UAV-SD dataset demonstrate that the CAS-Net is superior to other baseline CD networks. The CAS-Net detection accuracy is 93.1% on the UAV-SD dataset. The code and the dataset can be found at https://github.com/WenbaLi/CAS-Net .</p> | - |
dc.language | eng | - |
dc.publisher | IEEE | - |
dc.relation.ispartof | IEEE Transactions on Geoscience and Remote Sensing | - |
dc.rights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | - |
dc.subject | Change detection (CD) | - |
dc.subject | dataset | - |
dc.subject | Siamese network | - |
dc.subject | unmanned aerial vehicle (UAV) | - |
dc.title | CAS-Net: Comparison-Based Attention Siamese Network for Change Detection With an Open High-Resolution UAV Image Dataset | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TGRS.2024.3386918 | - |
dc.identifier.scopus | eid_2-s2.0-85190791941 | - |
dc.identifier.volume | 62 | - |
dc.identifier.spage | 1 | - |
dc.identifier.epage | 17 | - |
dc.identifier.eissn | 1558-0644 | - |
dc.identifier.issnl | 0196-2892 | - |