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
[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).
[12] C. Zuo et al. Transport of intensity equation: a tutorial. Opt. Lasers Eng., 135, 106187(2020).
[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).
Get Citation
Copy Citation Text
Kaiqiang Wang, Edmund Y. Lam, "Deep learning phase recovery: data-driven, physics-driven, or a combination of both?," Adv. Photon. Nexus 3, 056006 (2024)
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)