Laser & Optoelectronics Progress, Volume. 61, Issue 22, 2212004(2024)

Bulk Damage Point Detection in Crystals Based on Improved YOLOv8

Haojie Feng1, Jinfang Shi1、*, Rong Qiu2, Qiang Zhou2, Jianxin Wang2, Decheng Guo2, and Qing Wang2
Author Affiliations
  • 1School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, Sichuan , China
  • 2Joint Laboratory for Extreme Conditions Matter Properties, School of Mathematics and Physics, Southwest University of Science and Technology, Mianyang 621010, Sichuan , China
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    References(26)

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    [10] Wang N, Liu L T, Song X J et al. Subsurface defect detection method of optical elements based on through-focus scanning optical microscopy[J]. Acta Optica Sinica, 43, 122008(2023).

    [14] Feng B. Research on final optics damage online inspection technologies for ICF system[D](2014).

    [17] Liu Y. Application of convolutional neural network in optical element damage detection[J]. Computer Knowledge and Technology, 13, 178-182(2017).

    [20] Li Y, Li J L, Li Z et al. Inspection and repair of optical damage in tradition and deep learning(invited)[J]. Acta Photonica Sinica, 51, 1012002(2022).

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    Haojie Feng, Jinfang Shi, Rong Qiu, Qiang Zhou, Jianxin Wang, Decheng Guo, Qing Wang. Bulk Damage Point Detection in Crystals Based on Improved YOLOv8[J]. Laser & Optoelectronics Progress, 2024, 61(22): 2212004

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    Paper Information

    Category: Instrumentation, Measurement and Metrology

    Received: Jan. 23, 2024

    Accepted: Mar. 29, 2024

    Published Online: Nov. 13, 2024

    The Author Email: Jinfang Shi (603071939@qq.com)

    DOI:10.3788/LOP240590

    CSTR:32186.14.LOP240590

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