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Airborne point cloud classification integrating edge convolution and global-local self-attention
Information Sciences | 更新时间：2025-02-24
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    • Airborne point cloud classification integrating edge convolution and global-local self-attention

    • “In the field of 3D scene understanding, experts have proposed a new airborne point cloud classification method that effectively improves classification accuracy and provides a new solution to solve the problem of imbalanced sample categories.”
    • Optics and Precision Engineering   Vol. 32, Issue 24, Pages: 3658-3673(2024)

    • DOI：10.37188/OPE.20243224.3658    

      CLC： TN957.52

    • Received：08 July 2024，

      Revised：21 September 2024，

      Published：25 December 2024

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  • TU Jingmin,YAN Jin,LI Li,et al.Airborne point cloud classification integrating edge convolution and global-local self-attention[J].Optics and Precision Engineering,2024,32(24):3658-3673. DOI： 10.37188/OPE.20243224.3658.

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