Chinese Optics Letters, Volume. 18, Issue 5, 050602(2020)

Deep learning for position fixing in the micron scale by using convolutional neural networks

Hongye Li1, Hu Liang4, Qihao Hu1, Meng Wang1,2,3, and Zefeng Wang1,2,3、*
Author Affiliations
  • 1College of Advanced Interdisciplinary Studies, National University of Defense Technology, Changsha 410073, China
  • 2State Key Laboratory of Pulsed Power Laser Technology, Changsha 410073, China
  • 3Hunan Provincial Key Laboratory of High Energy Laser Technology, Changsha 410073, China
  • 4Tianjin Navigation Instruments Research Institute, Tianjin 300131, China
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    Figures & Tables(9)
    Schematic of offset splicing.
    Excitation efficiency of each fiber mode versus offset point (offset direction: x axis).
    Auto-correlation function of specklegrams: (a) offset point in the x direction varies from −25 μm to 25 μm; (b) offset point in the whole plane.
    Excitation ratio of (a) the third and (b) the seventh lower modes at different offset points.
    Specklegrams of two centrosymmetric offset points: (a) (6 μm, −5 μm) and (b) (−6 μm, 5 μm).
    (a) Data processing flow and (b) CNN architecture.
    Loss versus training epoch (loss, MSE in training set; and val_loss, MSE in validation set).
    Distribution of difference between the prediction label and validation label.
    Labeled offset points with d higher than 2 μm in the validation set.
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    Hongye Li, Hu Liang, Qihao Hu, Meng Wang, Zefeng Wang, "Deep learning for position fixing in the micron scale by using convolutional neural networks," Chin. Opt. Lett. 18, 050602 (2020)

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    Paper Information

    Category: Fiber Optics and Optical Communications

    Received: Dec. 3, 2019

    Accepted: Jan. 16, 2020

    Published Online: Apr. 28, 2020

    The Author Email: Zefeng Wang (hotrosemaths@163.com)

    DOI:10.3788/COL202018.050602

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