Photonics Research, Volume. 10, Issue 11, 2667(2022)

Optimize performance of a diffractive neural network by controlling the Fresnel number

Minjia Zheng1, Lei Shi1,2,3、*, and Jian Zi1,2,3,4
Author Affiliations
  • 1State Key Laboratory of Surface Physics, Key Laboratory of Micro- and Nano-Photonic Structures (Ministry of Education) and Department of Physics, Fudan University, Shanghai 200433, China
  • 2Institute for Nanoelectronic Devices and Quantum Computing, Fudan University, Shanghai 200433, China
  • 3Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, China
  • 4e-mail:
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    [11] A. Chaurasia, E. Culurciello. LinkNet: exploiting encoder representations for efficient semantic segmentation. IEEE Visual Communications and Image Processing (VCIP), 1-4(2017).

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    [21] P. R. Prucnal, B. J. Shastri, M. C. Teich. Neuromorphic Photonics(2017).

    [32] S. Pai, Z. Sun, T. W. Hughes, T. Park, B. Bartlett, I. A. D. Williamson, M. Minkov, M. Milanizadeh, N. Abebe, F. Morichetti, A. Melloni, S. Fan, O. Solgaard, D. A. B. Miller. Experimentally realized in situ backpropagation for deep learning in nanophotonic neural networks(2022).

    [53] R. W. Gerchberg, W. O. Saxton. A practical algorithm for the determination of plane from image and diffraction pictures. Optik, 35, 237-246(1972).

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    Minjia Zheng, Lei Shi, Jian Zi, "Optimize performance of a diffractive neural network by controlling the Fresnel number," Photonics Res. 10, 2667 (2022)

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    Paper Information

    Category: Image Processing and Image Analysis

    Received: Aug. 31, 2022

    Accepted: Sep. 20, 2022

    Published Online: Oct. 31, 2022

    The Author Email: Lei Shi (lshi@fudan.edu.cn)

    DOI:10.1364/PRJ.474535

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