计算机与数字工程2017，Vol.45Issue(7)：1373-1376,4.DOI:10.3969/j.issn.1672-9722.2017.07.030
基于云计算的基板玻璃缺陷神经网络分类模型研究
Study on Neural Network Classification Model of Substrate Glass Defects Based on Cloud Computing
摘要
Abstract
Identify types of glass substrate defects is an important basis for the adjustment and optimization of the production process.In this paper basic mode and principle of cloud computing are studied,combined with practical problems of LCD glass substrate production,based on cloud computing glass substrate defects classify model of neural network is designed,the allocation model in processing and transmission of data packets,machine scheduling,cloud computing server are studied briefly,the model has to enhance the convergence speed of neural network,the sharing of resources is realized,production efficiency,is improved redundant computation and algorithm of thermally are upgraded,the maintenance difficulty and other advantages are reduced.For the glass substrate manufacturer it has a certain reference value.关键词
基板玻璃/缺陷分类/云计算/神经网络/图像处理Key words
substrate glass/defect classification/cloud computing/neural network/image processing分类
信息技术与安全科学引用本文复制引用
李青,周波..基于云计算的基板玻璃缺陷神经网络分类模型研究[J].计算机与数字工程,2017,45(7):1373-1376,4.基金项目
国家科技支撑计划(编号:2013BAE03B02)资助. （编号:2013BAE03B02）
