• Technical Conference:  30 March – 03 April 2025
  • Exhibition: 01 – 03 April 2025
  • Moscone Center, San Francisco, California, USA
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Poster / Demo

Denoising in Mode Conversion by Utilizing Diffractive Deep Neural Networks Optimized With Reinforcement Learning (W2B.13)

Presenter: Zheng Li, Tianjin University

We propose a reinforcement-learning-optimized nonlinear physical diffractive neural network, which can simultaneously perform OAM-mode and LP-mode conversion with Gaussian noise removal. The PSNR and SSIM of the converted modes reach 27.94 dB and 0.838, respectively.

Authors:Zheng Li, Tianjin University / Wenbo Zhang, Tianjin University / Yang Wang, Tianjin University / Guanju Peng, Tianjin University / Zongze Li, Peng Cheng Laboratory / Xiaoyan Zhou, Tianjin University / Lin Zhang, Tianjin University

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