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    • FLGF UNet: Remote sensing building extraction network for optical remote sensing images that integrates local-global features

    • “The semantic segmentation of remote sensing images plays a significant role in urban change detection and other fields. Experts have proposed the FLGF UNet network, which integrates local and global features and adds an interactive fusion module to effectively solve problems such as missed and false detections in remote sensing building extraction, opening up new directions for research in related fields.”
      • role:First author第一作者
      • Affiliation:

        School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin 300384, China

      • Email:ligy@tcu.edu.cn
      • Introduction:李国燕,研究方向为机器视觉、下一代网络技术。E-mail: ligy@tcu.edu.cn

      LI Guoyan

      ,
      • Affiliation:

        School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin 300384, China

      LIU Tao

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

        School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin 300384, China

      • Email:wanglichengjian@tcu.edu.cn
      • Introduction:王丽,研究方向为智能传感。E-mail: wanglichengjian@tcu.edu.cn

      WANG Li

      * ,
      • Affiliation:

        School of Computer and Information Engineering, Tianjin Chengjian University, Tianjin 300384, China

      LIU Yi

    • Vol. 30, Issue 3, Pages: 696-709(2026)  
    • DOI:10.11834/jrs.20264516    

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