Evgenij M. Macheev, A. V. Devyatkin, Aleksandr R. Muzalevsky
{"title":"先进交通标志识别系统","authors":"Evgenij M. Macheev, A. V. Devyatkin, Aleksandr R. Muzalevsky","doi":"10.1109/scm55405.2022.9794877","DOIUrl":null,"url":null,"abstract":"Solving the problem of identifying and recognizing traffic signs is one of the most important research topics necessary for designing unmanned vehicles. The paper describes the general implementation of the sign detection subsystem and suggests a solution to the problem of the absence of individual traffic signs in open datasets based on the use of convolutional neural networks.","PeriodicalId":162457,"journal":{"name":"2022 XXV International Conference on Soft Computing and Measurements (SCM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Advanced Traffic Sign Recognition System\",\"authors\":\"Evgenij M. Macheev, A. V. Devyatkin, Aleksandr R. Muzalevsky\",\"doi\":\"10.1109/scm55405.2022.9794877\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Solving the problem of identifying and recognizing traffic signs is one of the most important research topics necessary for designing unmanned vehicles. The paper describes the general implementation of the sign detection subsystem and suggests a solution to the problem of the absence of individual traffic signs in open datasets based on the use of convolutional neural networks.\",\"PeriodicalId\":162457,\"journal\":{\"name\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-05-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 XXV International Conference on Soft Computing and Measurements (SCM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/scm55405.2022.9794877\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 XXV International Conference on Soft Computing and Measurements (SCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/scm55405.2022.9794877","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solving the problem of identifying and recognizing traffic signs is one of the most important research topics necessary for designing unmanned vehicles. The paper describes the general implementation of the sign detection subsystem and suggests a solution to the problem of the absence of individual traffic signs in open datasets based on the use of convolutional neural networks.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
