基于神经网络的MRC图像识别

Proceedings of 2013 2nd International Conference on Measurement, Information and Control Pub Date : 2013-08-01 DOI:10.1109/MIC.2013.6758137

L. Wenjuan, Cheng Huaiying, Wang Yuzhi, Fu Min

{"title":"基于神经网络的MRC图像识别","authors":"L. Wenjuan, Cheng Huaiying, Wang Yuzhi, Fu Min","doi":"10.1109/MIC.2013.6758137","DOIUrl":null,"url":null,"abstract":"Traditional image during MRC measurement needs eyes to judge, which exists the subjective error. This paper describes theoretical framework, design and testing process of objective measurement MRC. By using BP neural network model, MRC image can be recognized automatically and reduces subjective error. The experimental results show that three layers BP neural networks can effectively identify the image by choosing appropriate characteristic value.","PeriodicalId":404630,"journal":{"name":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"MRC image recognition based on neural network\",\"authors\":\"L. Wenjuan, Cheng Huaiying, Wang Yuzhi, Fu Min\",\"doi\":\"10.1109/MIC.2013.6758137\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Traditional image during MRC measurement needs eyes to judge, which exists the subjective error. This paper describes theoretical framework, design and testing process of objective measurement MRC. By using BP neural network model, MRC image can be recognized automatically and reduces subjective error. The experimental results show that three layers BP neural networks can effectively identify the image by choosing appropriate characteristic value.\",\"PeriodicalId\":404630,\"journal\":{\"name\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 2013 2nd International Conference on Measurement, Information and Control\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MIC.2013.6758137\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2013 2nd International Conference on Measurement, Information and Control","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MIC.2013.6758137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

传统的MRC测量图像需要人眼判断，存在主观误差。本文介绍了客观测量MRC的理论框架、设计和测试过程。利用BP神经网络模型实现MRC图像的自动识别，减少了主观误差。实验结果表明，通过选择合适的特征值，三层BP神经网络可以有效地识别图像。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

MRC image recognition based on neural network

Traditional image during MRC measurement needs eyes to judge, which exists the subjective error. This paper describes theoretical framework, design and testing process of objective measurement MRC. By using BP neural network model, MRC image can be recognized automatically and reduces subjective error. The experimental results show that three layers BP neural networks can effectively identify the image by choosing appropriate characteristic value.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Proceedings of 2013 2nd International Conference on Measurement, Information and Control

自引率

0.00%

发文量