人工智能
图像处理
计算机视觉
色空间
图像质量
数字图像处理
模式识别(心理学)
卷积神经网络
作者
Nadav Shabairou,Eyal Cohen,Omer Wagner,Dror Malka,Zeev Zalevsky
出处
期刊:Optics Letters
[The Optical Society]
日期:2018-11-15
卷期号:43 (22): 5603-5606
被引量:17
摘要
The rapid growth of applications that rely on artificial neural network (ANN) concepts gives rise to a staggering increase in the demand for hardware implementations of neural networks. New types of hardware that can support the requirements of high-speed associative computing while maintaining low power consumption are sought, and optical artificial neural networks fit the task well. Inherently, optical artificial neural networks can be faster, support larger bandwidth, and produce less heat than their electronic counterparts. Here we propose the design of an optical ANN-based imaging system that has the ability to self-study image signals from an incoherent light source in different colors. Our design consists of a combination of a multimode fiber and a multi-core optical fiber realizing a neural network. We show that the signals, transmitted through the multimode fiber, can be used for image identification purposes and can also be reconstructed using ANNs with a low number of nodes. An all-optical solution can then be achieved by realizing these networks with the multi-core optical neural network fiber.
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