Hyperspectral Object Identification | Views:1117Downloads:2352CSCD:1

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    • Hyperspectral image classification based on three branch network with grouped spatial-spectral attention

    • “In the field of hyperspectral image classification, researchers have proposed a three branch grouped spatial spectral attention deep network structure, which effectively extracts spatial and spectral information, and the experimental results are superior to existing advanced algorithms.”
      • role：First author第一作者
      • Affiliation：

        Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China

      • Email：suhan@stu.hubu.edu.cn
      • Introduction：苏涵，研究方向为图像处理。E-mail： suhan@stu.hubu.edu.cn

      SU Han

      1,
      • Affiliation：

        Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China

      CHEN Na

      1,
      • Affiliation：

        Hubei Key Laboratory of Applied Mathematics, Faculty of Mathematics and Statistics, Hubei University, Wuhan 430062, China

        Industrial Research Institute of Remote Sensing, Ningbo University, Shiye Intelligent Technology Co., Ltd, Ningbo 315211, China

      PENG Jiangtao

      13,
      • role：Corresponding author通信作者
      • Affiliation：

        Department of Geography and Spatial Information Techniques, Ningbo University, Ningbo 315211, China

        Industrial Research Institute of Remote Sensing, Ningbo University, Shiye Intelligent Technology Co., Ltd, Ningbo 315211, China

      • Email：sunweiwei@nbu.edu.cn
      • Introduction：孙伟伟，研究方向为多源遥感协同智能解译与海岸带健康监测。E-mail： sunweiwei@nbu.edu.cn

      SUN Weiwei

      23 *
    • Vol. 28, Issue 1, Pages: 247-265(2024)  

    • DOI：10.11834/jrs.20232492    

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