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    • Bifurcated attention and feature interaction for few-shot fine-grained learning

    • In the field of fine-grained image classification, researchers have proposed a small sample learning method with dual branch attention and feature interaction, which effectively improves classification performance and provides new ideas for fine-grained image recognition.
    • Vol. 30, Issue 5, Pages: 1419-1432(2025)   

      Received:06 August 2024

      Revised:29 September 2024

      Published:16 May 2025

    • DOI: 10.11834/jig.240429     

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  • Wen Lang, Gou Guanglei, Bai Ruifeng, Miao Wanyu. 2025. Bifurcated attention and feature interaction for few-shot fine-grained learning. Journal of Image and Graphics, 30(5):1419-1432 DOI: 10.11834/jig.240429.
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相关作者

Wen Lang 重庆理工大学计算机科学与工程学院
Gou Guanglei 重庆理工大学计算机科学与工程学院
Bai Ruifeng 重庆理工大学计算机科学与工程学院
Miao Wanyu 重庆理工大学计算机科学与工程学院
Wang Ziqi 陆军工程大学指挥控制工程学院
Li Yang 陆军工程大学指挥控制工程学院
Zhang Rui 陆军工程大学指挥控制工程学院
Wang Jiabao 陆军工程大学指挥控制工程学院

相关机构

Command and Control Engineering College, Army Engineering University of PLA
School of Computer Science, Sichuan Normal University
School of Computing and Artificial Intelligence, Southwest Jiaotong University
School of Business, Sichuan Normal University
School of Computer Science and Artificial Intelligence, Wuhan University of Technology
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