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    • Parameter-efficient fine-tuning for remote sensing image interpretation: a survey

    • Massive remote sensing data and AI models promote the implementation of intelligent remote sensing image interpretation, and "pre training+fine-tuning" has become a classic paradigm. Expert research suggests three major methods for fine-tuning keywords, adapter fine-tuning, and low rank adaptive fine-tuning, summarizing their performance and providing theoretical references and research ideas for the "AI+remote sensing" application ecosystem.
    • Vol. 31, Issue 1, Pages: 212-242(2026)   

      Received:23 April 2025

      Revised:2025-05-25

      Accepted:27 June 2025

      Published:16 January 2026

    • DOI: 10.11834/jig.250105     

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  • Chen Shiqi, Yang Xue, Zhu Rongqiang, Liao Ning, Zhao Weiwei. 2026. Parameter-efficient fine-tuning for remote sensing image interpretation: a survey. Journal of Image and Graphics, 31(1):0212-0242 DOI: 10.11834/jig.250105.
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相关作者

Chen Shiqi 信息支援部队工程大学
Yang Xue 上海交通大学自动化与感知学院
Zhu Rongqiang 上海交通大学计算机学院
Zhao Weiwei 信息支援部队工程大学

相关机构

College of Information and Communication, National University of Defense Technology
Department of Automation, Shanghai Jiao Tong University
上海交通大学计算机学院
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