可对可见光波长进行分类的宽带衍射神经网络

IF 3.7 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Ying Zhi Cheong, Litty Thekkekara, Madhu Bhaskaran, Blanca del Rosal, Sharath Sriram
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引用次数: 0

摘要

衍射神经网络 在编号为 2300310 的文章中,Ying Zhi Cheong、Blanca del Rosal、Sharath Sriram 及其合作者提出并展示了一种微型多层衍射神经网络方法,可对可见光谱中的各种波长进行分类。这种通过双光子聚合实现的微型分类方法可应用于医疗诊断和材料科学领域,根据特定波长的光学消光带的存在情况快速检测分析物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Broadband Diffractive Neural Networks Enabling Classification of Visible Wavelengths

Broadband Diffractive Neural Networks Enabling Classification of Visible Wavelengths

Diffractive Neural Networks

In article number 2300310, Ying Zhi Cheong, Blanca del Rosal, Sharath Sriram, and co-workers propose and demonstrate a microscale multi-layer diffractive neural network approach that classifies various wavelengths in the visible spectrum. This miniaturised classification approach, achieved through two-photon polymerization, has potential application in medical diagnosis to material science, enabling rapid detection of analytes based on the presence of optical extinction bands at specific wavelengths.

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