基于相变材料微环混合波导的高分辨率光学卷积神经网络

IF 3.7 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Advanced Photonics Research Pub Date : 2024-12-05 DOI:10.1002/adpr.202470033

Shuguang Zhu, Zhengyang Zhang, Weiwei Tang, Leijun Xu, Li Han, Jie Hong, Yiming Yu, Ziying Li, Qinghua Qin, Changlong Liu, Libo Zhang, Songyuan Ding, Jiale He, Guanhai Li, Xiaoshuang Chen

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引用次数: 0

摘要

光学卷积神经网络在编号为 2400108 的文章中，谭维维、何佳乐、李冠海、陈晓双及其合作者提出了一种光学神经网络，该网络利用基于 GST 的微孔波导进行片上计算，可提供 64 级传输对比度和 6 位分辨率。它在图像边缘检测和识别方面实现了高精度，具有大规模光子神经网络的潜力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

High-Resolution Optical Convolutional Neural Networks Using Phase-Change Material-Based Microring Hybrid Waveguides

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High-Resolution Optical Convolutional Neural Networks Using Phase-Change Material-Based Microring Hybrid Waveguides

Optical Convolutional Neural Networks

In article number 2400108, Weiwei Tan, Jiale He, Guanhai Li, Xiaoshuang Chen, and co-workers propose an optical neural network that leverages GST-based microring waveguides for on-chip computing, offering 64 levels of transmission contrast with 6-bit resolution. It achieves high accuracy in image edge detection and recognition with potential for large-scale photonic neural networks.

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来源期刊

Advanced Photonics Research

自引率

2.70%

发文量