Remote Sensing Intelligent Interpretation | Views:1278Downloads:3679CSCD:2

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    • High resolution remote sensing image segmentation based on dual-modal efficient feature learning

    • “In the field of remote sensing image segmentation, experts have proposed a high-resolution remote sensing image segmentation algorithm based on bimodal feature learning, which effectively improves segmentation accuracy.”
      • role：First author第一作者
      • Affiliation：

        School of Electronic and Information Engineering, Wuxi University, Wuxi 214105, China

        School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

      • Email：yorkzhang@nuist.edu.cn
      • Introduction：张银胜，研究方向为遥感图像处理、深度学习。E-mail： yorkzhang@nuist.edu.cn

      ZHANG Yinsheng

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

        School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

      • Email：20211249643@nuist.edu.cn
      • Introduction：吉茹，研究方向为遥感图像分割、深度学习。E-mail： 20211249643@nuist.edu.cn

      JI Ru

      2 * ,
      • Affiliation：

        School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

      TONG Junyi

      2,
      • Affiliation：

        School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

      YANG Yulong

      2,
      • Affiliation：

        School of Electronic and Information Engineering, Wuxi University, Wuxi 214105, China

      HU Yuxiang

      1,
      • Affiliation：

        School of Electronic and Information Engineering, Wuxi University, Wuxi 214105, China

        School of Electronic and Information Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China

      SHAN Huilin

      12
    • Vol. 28, Issue 2, Pages: 481-493(2024)  

    • DOI：10.11834/jrs.20233162    

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