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    • Boundary-guided and shape-aware semi-supervised semantic segmentation for remote sensing image

    • In the field of semi supervised segmentation of remote sensing images, researchers have proposed BS5 Net, which effectively improves feature discrimination and boundary segmentation capabilities, optimizes the quality of pseudo label generation, improves utilization, and outperforms existing advanced methods in performance.
    • Pages: 1-15(2026)   

      Received:13 November 2025

      Revised:2026-01-19

      Accepted:21 January 2026

      Published Online:21 January 2026

    • DOI: 10.11834/jig.250575     

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  • Rong Yu, Lin Hui, Hang Renlong. Boundary-guided and shape-aware semi-supervised semantic segmentation for remote sensing image[J/OL]. Journal of Image and Graphics, 2026, 1-15. DOI: 10.11834/jig.250575.
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相关作者

Li Linjuan 太原科技大学电子信息工程学院;先进控制与装备智能化山西省重点实验室
He Yun 太原科技大学电子信息工程学院
Xie Gang 太原科技大学电子信息工程学院;先进控制与装备智能化山西省重点实验室
Zhang Haoxue 太原科技大学电子信息工程学院;先进控制与装备智能化山西省重点实验室
Bai Yanhong 太原科技大学电子信息工程学院
Wei Hu 北京化工大学信息科学与技术学院
Bochuan Gao 北京化工大学信息科学与技术学院
Zhenhang Huang 北京化工大学信息科学与技术学院

相关机构

School of Electronic Information Engineering, Taiyuan University of Science and Technology
Shanxi Key Laboratory of Advanced Control and Equipment Intelligence
College of Information Science and Technology, Beijing University of Chemical Technology
School of Computer Science and Technology / School of Artificial Intelligence, China University of Mining and Technology
Mine Digitization Engineering Research Center of the Ministry of Education
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