首页|一种基于混合量子——经典神经网络模型预测光学成像系统成像质量的方法

一种基于混合量子——经典神经网络模型预测光学成像系统成像质量的方法

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光学成像系统广泛应用于生活中,由于长期暴露于环境中,相机寿命会受到一定的影响.本文分析了随着气体腐蚀过程中光学成像系统成像质量的灰阶值变化,并利用灰阶值定义了老化前后相机拍摄的图片.通过混合量子-经典神经网络模型对相机的成像质量进行学习,能很好的对光学成像系统的成像质量进行预测,对老化的系统进行提前预警.
A Method for Predicting the Imaging Quality of An Optical Imaging System Based on A Hybrid Quantum-Classical Neural Network Model
Optical imaging systems are widely used in daily life.Due to long-term exposure to the environment,the life of the camera will be affected.This paper analyzes the gray scale value change of the imaging quality of the optical imaging system during the gas corrosion process,and uses the gray scale value to define the pictures taken by the camera before and after aging.Learning the imaging quality of the camera through the hybrid quantum-classical neural network model can predict the imaging quality of the optical system well and give early warning to the aging system.

quantum hybiryd algorithmoptical imaging system

王忠、王婷婷

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中国合格评定国家认可中心,北京 100063

上海市质量监督检验技术研究院,上海 201114

量子经典混合算法 光学成像系统

2024

环境技术
广州电器科学研究院有限公司

环境技术

CSTPCD
影响因子:0.995
ISSN:1004-7204
年,卷(期):2024.42(12)