{"title":"基于神经网络技术的车牌识别应用的开发","authors":"V. Varkentin, Maxim Schukin","doi":"10.1109/IT&QM&IS.2019.8928373","DOIUrl":null,"url":null,"abstract":"The abstract task of recognizing vehicle license plates one from another has become relevant with the general increase of number of vehicles. There were 373 cars per 1,000 people in Russia in 2018. Identification of the vehicle number can be used for various purposes: control of traffic rules, automatic calculation of fines, control of movement of a specific vehicle, etc. There are many solutions to the problem of recognizing the license plate number, including online services. The recognition level of existing tools allows you to fully automate this process and achieve a high level of recognition accuracy. The most promising approach to solving this problem is the use of neural network technologies. This article discusses the development of an application for license plate recognition using neural network technologies.","PeriodicalId":285904,"journal":{"name":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","volume":"359 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Development of an Application for Car License Plates Recognition Using Neural Network Technologies\",\"authors\":\"V. Varkentin, Maxim Schukin\",\"doi\":\"10.1109/IT&QM&IS.2019.8928373\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The abstract task of recognizing vehicle license plates one from another has become relevant with the general increase of number of vehicles. There were 373 cars per 1,000 people in Russia in 2018. Identification of the vehicle number can be used for various purposes: control of traffic rules, automatic calculation of fines, control of movement of a specific vehicle, etc. There are many solutions to the problem of recognizing the license plate number, including online services. The recognition level of existing tools allows you to fully automate this process and achieve a high level of recognition accuracy. The most promising approach to solving this problem is the use of neural network technologies. This article discusses the development of an application for license plate recognition using neural network technologies.\",\"PeriodicalId\":285904,\"journal\":{\"name\":\"2019 International Conference \\\"Quality Management, Transport and Information Security, Information Technologies\\\" (IT&QM&IS)\",\"volume\":\"359 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference \\\"Quality Management, Transport and Information Security, Information Technologies\\\" (IT&QM&IS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IT&QM&IS.2019.8928373\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference \"Quality Management, Transport and Information Security, Information Technologies\" (IT&QM&IS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IT&QM&IS.2019.8928373","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Development of an Application for Car License Plates Recognition Using Neural Network Technologies
The abstract task of recognizing vehicle license plates one from another has become relevant with the general increase of number of vehicles. There were 373 cars per 1,000 people in Russia in 2018. Identification of the vehicle number can be used for various purposes: control of traffic rules, automatic calculation of fines, control of movement of a specific vehicle, etc. There are many solutions to the problem of recognizing the license plate number, including online services. The recognition level of existing tools allows you to fully automate this process and achieve a high level of recognition accuracy. The most promising approach to solving this problem is the use of neural network technologies. This article discusses the development of an application for license plate recognition using neural network technologies.