• High Power Laser and Particle Beams
  • Vol. 34, Issue 6, 064002 (2022)
Dong Li, Liang Sheng, Yang Li, and Baojun Duan
Author Affiliations
  • State Key Laboratory of Intense Pulsed Radiation Simulation and Effect, Northwest Institute of Nuclear Technology, Xi’an 710024, China
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    DOI: 10.11884/HPLPB202234.210345 Cite this Article
    Dong Li, Liang Sheng, Yang Li, Baojun Duan. Research on algorithm for restoration of large aperture and thick pinhole imaging based on neural network[J]. High Power Laser and Particle Beams, 2022, 34(6): 064002 Copy Citation Text show less
    References

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    [5] Simonyan K, Zisserman A. Very deep convolutional wks f largescale image recognition[J]. Computer Science, 2014.

    [6] He K , Zhang X , Ren S , et al. Deep residual learning f image recognition[C]2016 IEEE Conference on Computer Vision Pattern Recognition (CVPR). 2016: 770778.

    [7] Szegedy C, Liu W, Jia Y, et al. Going deeper with convolutions[M]. IEEE Computer Society, 2014.

    [8] Kai Z, Zuo W, Chen Y, et al. Beyond a Gaussian denoiser: Residual learning of deep CNN for image denoising[J]. IEEE Transactions on Image Processing, 26, 3142-3155(2016).

    [10] Pan S J, Qiang Y. A survey on transfer learning[J]. IEEE Transactions on Knowledge and Data Engineering, 22, 1345-1359(2010).

    Dong Li, Liang Sheng, Yang Li, Baojun Duan. Research on algorithm for restoration of large aperture and thick pinhole imaging based on neural network[J]. High Power Laser and Particle Beams, 2022, 34(6): 064002
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