• Chinese Journal of Lasers
  • Vol. 50, Issue 11, 1101009 (2023)
Yiwen Hu1, Xin Liu1, Cuifang Kuang1、2, Xu Liu1、2, and Xiang Hao1、*
Author Affiliations
  • 1College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, Zhejiang, China
  • 2Research Center for Intelligent Sensing, Zhejiang Lab, Hangzhou 311100, Zhejiang, China
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    DOI: 10.3788/CJL230470 Cite this Article Set citation alerts
    Yiwen Hu, Xin Liu, Cuifang Kuang, Xu Liu, Xiang Hao. Research Progress and Prospect of Adaptive Optics Based on Deep Learning[J]. Chinese Journal of Lasers, 2023, 50(11): 1101009 Copy Citation Text show less
    Commonly used artificial neural network models. (a) Fully connected neural network; (b) convolutional neural network; (c) residual network; (d) U-Net architecture; (e) Inception architecture; (f) long short-term memory network
    Fig. 1. Commonly used artificial neural network models. (a) Fully connected neural network; (b) convolutional neural network; (c) residual network; (d) U-Net architecture; (e) Inception architecture; (f) long short-term memory network
    Commonly used activation function. (a) ReLU function; (b) sigmoid function; (c) tanh function
    Fig. 2. Commonly used activation function. (a) ReLU function; (b) sigmoid function; (c) tanh function
    Structure of CNN7 model[34]
    Fig. 3. Structure of CNN7 model[34]
    Training architecture of weights-sharing two-stream CNN framework[42]
    Fig. 4. Training architecture of weights-sharing two-stream CNN framework[42]
    Sketch map of feature-based wavefront retrieval approach[47]
    Fig. 5. Sketch map of feature-based wavefront retrieval approach[47]
    Simulation results of reconstruction images [49]
    Fig. 6. Simulation results of reconstruction images [49]
    False rates of different methods under low signal-to-noise ratio [52]
    Fig. 7. False rates of different methods under low signal-to-noise ratio [52]
    ISNet architecture[57]
    Fig. 8. ISNet architecture[57]
    Architecture of SH-Net[59]. (a) Process of phase retrieval; (b) residual block architecture
    Fig. 9. Architecture of SH-Net[59]. (a) Process of phase retrieval; (b) residual block architecture
    Diffractive neural network
    Fig. 10. Diffractive neural network
    Yiwen Hu, Xin Liu, Cuifang Kuang, Xu Liu, Xiang Hao. Research Progress and Prospect of Adaptive Optics Based on Deep Learning[J]. Chinese Journal of Lasers, 2023, 50(11): 1101009
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