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    • Few-shot earth surface anomaly detection via large vision-language models

    • “In recent years, sudden surface anomalies have occurred frequently. To address the problem of insufficient annotated samples in the early stages of sudden anomalies, a lightweight small sample surface anomaly detection method based on a visual language pre training model is proposed, providing a solution to the problem of remote sensing emergency monitoring.”
      • role:First author第一作者
      • Affiliation:

        College of Geomatics, Xi'an University of Science and Technology, Xi'an 710054, China

      • Email:jihong36@xust.edu.cn
      • Introduction:冀虹,研究方向为计算机视觉与遥感图像处理。E-mail:jihong36@xust.edu.cn

      JI Hong

      1,
      • role:Corresponding author通信作者
      • Affiliation:

        School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430072, China

      • Email:gaozhinus@gmail.com
      • Introduction:高智,研究方向为计算机视觉、机器学习与遥感。E-mail:gaozhinus@gmail.com

      GAO Zhi

      2 * ,
      • Affiliation:

        Faculty of Geographical Science, Beijing Normal University, Beijing 100091, China

      WANG Qiao

      3
    • Pages: 1-18(2026)  
    • DOI:10.11834/jrs.20266048    

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