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    • From general segmentation to specialized building extraction——research on the optimization strategies of SAM in high-resolution remote sensing images

    • Related research has made new progress in the field of remote sensing image building extraction. Experts have proposed a no hint discrimination joint model (SAM Classifier), which realizes the transfer of general visual models to remote sensing scenes, completes the automated and efficient extraction of buildings, and provides a new solution to solve the accuracy bottleneck problem of traditional methods.
    • Vol. 31, Issue 2, Pages: 642-656(2026)   

      Received:24 June 2025

      Revised:2025-09-10

      Accepted:11 September 2025

      Published:16 February 2026

    • DOI: 10.11834/jig.250258     

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  • Chen Xiuxiu, Jin Yongsheng, Ye Jiansheng, Fang Lei. 2026. From general segmentation to specialized building extraction——research on the optimization strategies of SAM in high-resolution remote sensing images. Journal of Image and Graphics, 31(2):0642-0656 DOI: 10.11834/jig.250258.
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相关作者

Chen Xiuxiu 浙江大学建筑工程学院;浙大城市学院国土空间规划学院
Jin Yongsheng 铜陵有色股份铜冠黄铜棒材有限公司
Ye Jiansheng 杭州中房信息科技有限公司
Fang Lei 复旦大学 环境科学与工程系
Ai Bing 华北电力大学电子与通信工程系
Sun Zheng 华北电力大学电子与通信工程系;华北电力大学河北省电力物联网技术重点实验室
Hou Yingsa 华北电力大学电子与通信工程系
Sun Meichen 华北电力大学电子与通信工程系

相关机构

Hangzhou Jointfounder Information Technology Co., Ltd
Department of Electronic and Communication Engineering, North China Electric Power University
Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University
School of Computer Science,Fudan University
Institute of Automation, Chinese Academy of Sciences
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