Overcoming Hardware Imperfections in Optical Neural Networks Through a Machine Learning-Driven Self-Correction Mechanism

Overcoming Hardware Imperfections in Optical Neural Networks Through a Machine Learning-Driven Self-Correction Mechanism

We developed an optical neural network (ONN) for efficient processing and recognition of 2-dimensional (2D) images, employing a conventional liquid crystal display panel as optical neurons and synapses. This configuration allowed for optical signal outputs proportional to matrix-vector multiplicatio...

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Bibliographic Details
Main Authors: Minjoo Kim, Beomju Kim, Yelim Kim, Lia Saptini Handriani, Suhee Jang, Dae Yeop Jeong, Sung Ik Yang, Won Il Park
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Photonics Journal
Subjects:
Hardware imperfections
matrix-vector multiplication (MVM)
optical neural networks (ONNs)
recognition accuracy
self-correction approach
training algorithm
Online Access:https://ieeexplore.ieee.org/document/10420458/
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