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crossrefPhotonics2025-05-09Cited by 2

Machine Learning Applied to Optical Communication Systems

Zhaopeng Xu, Jinlong Wei

As the global demand for high-speed and high-capacity communication continues to surge, driven by cloud computing, artificial intelligence, 5G, virtual reality, and the Internet of Things (IoT), optical communication systems have emerged as the backbone of modern digital infrastructure [...]

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crossrefPhotonics2026-02-08

A Deep Learning-Enhanced MIMO C-OOK Scheme for Optical Camera Communication in Internet of Things Networks

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crossrefPhotonics2025-09-29Cited by 1

Robust and Interpretable Machine Learning for Network Quality Prediction with Noisy and Incomplete Data

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Accurate classification of optical communication signal quality is crucial for maintaining the reliability and performance of high-speed communication networks. While existing supervised learning approaches achieve high accuracy on laboratory-collected datasets, they often face d…

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crossrefPhotonics2025-03-07Cited by 6

Temperature Control Performance Improvement of High-Power Laser Diode with Assistance of Machine Learning

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For a laser diode (LD) with high output power, it is difficult to precisely and quickly control its temperature because of the large thermal power involved. In this paper, a machine learning-based temperature controller for high-power LDs is reported. It is implemented by develop…

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crossrefPhotonics2024-10-26Cited by 3

D-Band 4.6 km 2 × 2 MIMO Photonic-Assisted Terahertz Wireless Communication Utilizing Iterative Pruning Deep Neural Network-Based Nonlinear Equalization

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Polarization-Based Digital Histology of Human Skin Biopsies Assisted by Deep Learning

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Mueller polarimetry has proven to be a powerful optical technique to complement medical doctors in their conventional histology analysis. In this work, various degenerative and malignant human skin lesions were evaluated ex vivo using imaging Mueller polarimetry. The Mueller matr…

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