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    • Lightweight pyramid cross-attention network for orbital image defect detection

    • In the field of track defect detection, researchers have proposed the LPCANet model, which effectively improves detection speed and accuracy and has practical application value.
    • Vol. 30, Issue 12, Pages: 3824-3837(2025)   

      Received:24 September 2024

      Revised:2025-05-20

      Accepted:10 June 2025

      Published:16 December 2025

    • DOI: 10.11834/jig.240547     

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  • Guo Sixu, Geng Huizheng, Su Li, He Shen, Zhang Xinyue. 2025. Lightweight pyramid cross-attention network for orbital image defect detection. Journal of Image and Graphics, 30(12):3824-3837 DOI: 10.11834/jig.240547.
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相关作者

Guo Sixu 中国移动通信有限公司研究院;大连交通大学
Geng Huizheng 中国移动通信有限公司研究院
Su Li 中国移动通信有限公司研究院
He Shen 中国移动通信有限公司研究院
Zhang Xinyue 中国移动通信有限公司研究院
Hao Wen 西安理工大学计算机科学与工程学院;陕西省网络计算与安全技术重点实验室
Zuo Zhanbin 西安理工大学计算机科学与工程学院
Lu Hansen 西安理工大学计算机科学与工程学院

相关机构

Dalian Jiaotong University
Department of Computer Science,Xi’an University of Technology
Shaanxi Key Laboratory for Network Computing and Security Technology
School of Computer Science,Northwestern Polytechnical University
School of Computer and Information Technology, Shanxi University
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