Chinese Journal of Lasers, Volume. 51, Issue 17, 1710002(2024)

Semantic Segmentation of Large‑Scale Laser Point Cloud in Mines Based on Local Feature Enhancement

Hongxiang Dong1, Yi An1,2、*, Lirong Xie1, Zhiyong Yang3, and Kai Zhang1
Author Affiliations
  • 1School of Electrical Engineering, Xinjiang University, Urumqi 830017, Xinjiang , China
  • 2School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, Liaoning , China
  • 3Xinjiang Tianchi Energy Co., Ltd., Fukang831500, Xinjiang , China
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    References(24)

    [2] Li S, Xue G Z, Fang X Q et al. Coal mine intelligent safety system and key technologies[J]. Journal of China Coal Society, 45, 2320-2330(2020).

    [3] Yu H X, Du Z Y, Wei Z D et al. Analysis on the current situation and development trend of unmanned driving technology in mining areas in China[J]. Journal of Mine Automation, 48, 82-87(2022).

    [4] Chen Q Y, Xu T, Liu L Q et al. A LiDAR ranging system with integrated near-infrared SPAD array[J]. Acta Optica Sinica, 44, 1228001(2024).

    [5] Zhang P F, Han L T, Feng H J et al. Semantic segmentation of point cloud based on attention mechanism and global feature optimization[J]. Journal of Computer Applications, 44, 1086-1092(2024).

    [15] Qi C R, Yi L, Su H et al. PointNet++: deep hierarchical feature learning on point sets in a metric space[C], 5105-5114(2017).

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    Hongxiang Dong, Yi An, Lirong Xie, Zhiyong Yang, Kai Zhang. Semantic Segmentation of Large‑Scale Laser Point Cloud in Mines Based on Local Feature Enhancement[J]. Chinese Journal of Lasers, 2024, 51(17): 1710002

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    Paper Information

    Category: remote sensing and sensor

    Received: Nov. 22, 2023

    Accepted: Feb. 19, 2024

    Published Online: Aug. 29, 2024

    The Author Email: An Yi (anyi@dlut.edu.cn)

    DOI:10.3788/CJL231425

    CSTR:32183.14.CJL231425

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