Advanced Photonics Nexus, Volume. 3, Issue 5, 056006(2024)

Deep learning phase recovery: data-driven, physics-driven, or a combination of both? Editors' Pick , Author Presentation

Kaiqiang Wang* and Edmund Y. Lam*
Author Affiliations
  • University of Hong Kong, Department of Electrical and Electronic Engineering, Hong Kong, China
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    References(58)

    [3] R. K. Tyson, B. W. Frazier. Principles of Adaptive Optics(2022).

    [5] R. Leach. Optical Measurement of Surface Topography(2011).

    [8] J. W. Goodman. Introduction to Fourier Optics(2017).

    [9] J. Hartmann. Bermerkungen über den bau und die justierung von spektrographen. Z. Instrumentenkd., 20, 47-58(1900).

    [32] X. Shu et al. NAS-PRNet: neural architecture search generated phase retrieval net for off-axis quantitative phase imaging(2022).

    [38] L. Boominathan et al. Phase retrieval for Fourier ptychography under varying amount of measurements(2018).

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    Kaiqiang Wang, Edmund Y. Lam, "Deep learning phase recovery: data-driven, physics-driven, or a combination of both?," Adv. Photon. Nexus 3, 056006 (2024)

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    Paper Information

    Category: Research Articles

    Received: May. 9, 2024

    Accepted: Aug. 12, 2024

    Published Online: Sep. 18, 2024

    The Author Email: Wang Kaiqiang (kqwang.optics@gmail.com), Lam Edmund Y. (elam@eee.hku.hk)

    DOI:10.1117/1.APN.3.5.056006

    CSTR:32397.14.1.APN.3.5.056006

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