Journal of Applied Optics, Volume. 44, Issue 3, 677(2023)

Image classification of optical element surface defects based on convolutional neural network

Jinyao HOU1... Weiguo LIU1,*, Shun ZHOU1, Aihua GAO1, Shaobo GE1 and Xiangguo XIAO2 |Show fewer author(s)
Author Affiliations
  • 1College of Photoelectric Engineering, Xi'an Technological University, Xi'an 710021, China
  • 2Xi'an Institute of Applied Optics, Xi'an 710065, China
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    References(5)

    [4] [4] LIU Dong, YAGN Yongying, WANG Lin, et al. Microscopic scattering imaging measurement and digital evaluation system of defects for fine optical surface[J].Optics Communications, 2007, 278(2): 240-246.

    [7] [7] WANG Kungjeng, HAO Fanjiang, LEE Yaxuan, A multiple-stage defect detection model by convolutional neural network[J]. Computers & Industrial Engineering, 2022, 168: 108096.

    [15] [15] Makantasis K, Karantzalos K, Doulamis A, et al. Deep supervised learning for hyperspectral data classification through convolutional neural networks[C]// Geoscience & Remote Sensing Symposium.USA: IEEE, 2015: 4959-4962.

    [16] [16] BANDHU A, ROY S S. Classifying multi-category imagesusing deep learning: a convolutional neural network model[C]//IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology. Ban- galore: IEEE,2017: 915-919.

    [18] [18] DING X, GUO Y, DING G, et al. ACNet: strengthening the kernel skeletons for powerful CNN via asymmetric convolution blocks[C]// International Conference on Computer Vision, USA: IEEE, 2019: 1911-1920.

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    Jinyao HOU, Weiguo LIU, Shun ZHOU, Aihua GAO, Shaobo GE, Xiangguo XIAO. Image classification of optical element surface defects based on convolutional neural network[J]. Journal of Applied Optics, 2023, 44(3): 677

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    Paper Information

    Category: Research Articles

    Received: May. 30, 2022

    Accepted: --

    Published Online: Jun. 19, 2023

    The Author Email: LIU Weiguo (wgliu@163.com)

    DOI:10.5768/JAO202344.0305003

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