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    Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning

    New search for: Huang, Shuowen
    New search for: Hu, Qingwu
    New search for: Ai, Mingyao
    New search for: Zhao, Pengcheng
    New search for: Li, Jian
    New search for: Cui, Hao
    New search for: Wang, Shaohua

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    Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning

    New search for: Huang, Shuowen
    New search for: Hu, Qingwu
    New search for: Ai, Mingyao
    New search for: Zhao, Pengcheng
    New search for: Li, Jian
    New search for: Cui, Hao
    New search for: Wang, Shaohua

    Access

    Check access
    Check availability in my library
    Order at Subito €

    Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning

    New search for: Huang, Shuowen
    New search for: Hu, Qingwu
    New search for: Ai, Mingyao
    New search for: Zhao, Pengcheng
    New search for: Li, Jian
    New search for: Cui, Hao
    New search for: Wang, Shaohua

    Access

    Check access
    Check availability in my library
    Order at Subito €

    Access

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    Check availability in my library
    Order at Subito €

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    Document information
    Title:

    Weakly supervised 3D point cloud semantic segmentation for architectural heritage using teacher-guided consistency and contrast learning

    Additional title:

    Automation in Construction

    Contributors:

    Huang, Shuowen (author) / Hu, Qingwu (author) / Ai, Mingyao (author) / Zhao, Pengcheng (author) / Li, Jian (author) / Cui, Hao (author) / Wang, Shaohua (author)

    Published in:

    Automation in Construction ; 168 ; 105831

    Publication date:

    2024-12-01

    ISSN:

    0926-5805

    DOI:

    https://doi.org/10.1016/j.autcon.2024.105831

    Type of media:

    Article (Journal)

    Type of material:

    Electronic Resource

    Language:

    English

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