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    • JAM-R-CNN deep learning network model for remote sensing recognition of terraced fields

      • role:First author第一作者
      • Affiliation:

        College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China

        Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China

      • Email:xjy959@mails.ccnu.edu.cn
      • Introduction:谢君洋,研究方向为农业遥感。E-mail: xjy959@mails.ccnu.edu.cn

      XIE Junyang

      12,
      • Affiliation:

        College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China

        Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China

      LIN Anqi

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

        College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China

        Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China

      • Email:haowu@ccnu.edu.cn
      • Introduction:吴浩,研究方向为地理信息科学与遥感。E-mail: haowu@ccnu.edu.cn

      WU Hao

      12 * ,
      • Affiliation:

        College of Urban and Environmental Sciences, Central China Normal University, Wuhan 430079, China

        Hubei Province Key Laboratory for Geographical Process Analysis and Simulation, Wuhan 430079, China

      WU Ziwei

      12,
      • Affiliation:

        Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

      WU Wenbin

      3,
      • Affiliation:

        Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China

      YU Qiangyi

      3
    • Vol. 28, Issue 12, Pages: 3136-3146(2024)  
    • DOI:10.11834/jrs.20233126    

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LIN Anqi 华中师范大学 城市与环境科学学院;地理过程分析与模拟湖北省重点实验室
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