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    • Remote sensing target detection by fusing improved retinex image enhancement and adaptive label assignment

    • “Researchers have improved the YOLOv9 detector and developed an efficient and accurate remote sensing image rotation target detector RSO-YOLO, with a comprehensive detection accuracy of 81.1% mAP ranking first, balancing speed and accuracy, providing engineering implementation solutions for remote sensing scenarios such as maritime monitoring and urban management.”
      • role：First author第一作者
      • Affiliation：

        School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110023, China

      • Email：huanghu@smail.sut.edu.cn
      • Introduction：黄虎，研究方向为机器视觉与图像处理。E-mail： huanghu@smail.sut.edu.cn

      HUANG Hu

      1,
      • Affiliation：

        School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110023, China

        Shenyang Mxnavi Co., Ltd., Shenyang 110169, China

      ZHENG Hunan

      12,
      • role：Corresponding author通信作者
      • Affiliation：

        School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110023, China

      • Email：TangFei@sut.edu.cn
      • Introduction：唐非，研究方向为复杂系统建模与算法优化、大数据分析。E-mail： TangFei@sut.edu.cn

      TANG Fei

      1 * ,
      • Affiliation：

        School of Artificial Intelligence, Shenyang University of Technology, Shenyang 110023, China

      LI Chenyi

      1
    • Vol. 29, Issue 9, Pages: 2823-2840(2025)  

    • DOI：10.11834/jrs.20254153    

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