Megha Vamsi Kiran Choda, Sri Vardhan Perla, Brahmender Shaik, Yuva Teja Anirudh Yelchuru, P. Yalla
{"title":"基于CNN机器学习算法的实时交通标志识别关键研究","authors":"Megha Vamsi Kiran Choda, Sri Vardhan Perla, Brahmender Shaik, Yuva Teja Anirudh Yelchuru, P. Yalla","doi":"10.1109/IDCIoT56793.2023.10053394","DOIUrl":null,"url":null,"abstract":"Real-Time Traffic Sign Recognition System (RTTSRS) is used for recognizing the traffic signboards (Take left, take right, speed limit 60 kmph… etc.), it plays a crucial role in the domains of driverless vehicles etc. By using Real-Time Traffic Sign Recognition, Traffic related problems can be reduced. It is categorized into two types- localization and recognition. Localization deals with identifying and locating traffic sign regions within the radius. Real-Time Traffic Sign Recognition is used to identify the traffic sign region within the space (rectangular) provided. This study describes an approach for a traffic sign recognition system, many machine learning algorithms like Support Vector Machine (SVM) and Convolutional Neural Networks (CNN) have been studied for recognizing traffic signs. This study has conducted a critical investigation on various machine learning algorithms which gives high accuracy to predict, recognize real-time traffic signs.","PeriodicalId":60583,"journal":{"name":"物联网技术","volume":"20 1","pages":"445-450"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A Critical Survey on Real-Time Traffic Sign Recognition by using CNN Machine Learning Algorithm\",\"authors\":\"Megha Vamsi Kiran Choda, Sri Vardhan Perla, Brahmender Shaik, Yuva Teja Anirudh Yelchuru, P. Yalla\",\"doi\":\"10.1109/IDCIoT56793.2023.10053394\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Real-Time Traffic Sign Recognition System (RTTSRS) is used for recognizing the traffic signboards (Take left, take right, speed limit 60 kmph… etc.), it plays a crucial role in the domains of driverless vehicles etc. By using Real-Time Traffic Sign Recognition, Traffic related problems can be reduced. It is categorized into two types- localization and recognition. Localization deals with identifying and locating traffic sign regions within the radius. Real-Time Traffic Sign Recognition is used to identify the traffic sign region within the space (rectangular) provided. This study describes an approach for a traffic sign recognition system, many machine learning algorithms like Support Vector Machine (SVM) and Convolutional Neural Networks (CNN) have been studied for recognizing traffic signs. This study has conducted a critical investigation on various machine learning algorithms which gives high accuracy to predict, recognize real-time traffic signs.\",\"PeriodicalId\":60583,\"journal\":{\"name\":\"物联网技术\",\"volume\":\"20 1\",\"pages\":\"445-450\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"物联网技术\",\"FirstCategoryId\":\"1093\",\"ListUrlMain\":\"https://doi.org/10.1109/IDCIoT56793.2023.10053394\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"物联网技术","FirstCategoryId":"1093","ListUrlMain":"https://doi.org/10.1109/IDCIoT56793.2023.10053394","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Critical Survey on Real-Time Traffic Sign Recognition by using CNN Machine Learning Algorithm
Real-Time Traffic Sign Recognition System (RTTSRS) is used for recognizing the traffic signboards (Take left, take right, speed limit 60 kmph… etc.), it plays a crucial role in the domains of driverless vehicles etc. By using Real-Time Traffic Sign Recognition, Traffic related problems can be reduced. It is categorized into two types- localization and recognition. Localization deals with identifying and locating traffic sign regions within the radius. Real-Time Traffic Sign Recognition is used to identify the traffic sign region within the space (rectangular) provided. This study describes an approach for a traffic sign recognition system, many machine learning algorithms like Support Vector Machine (SVM) and Convolutional Neural Networks (CNN) have been studied for recognizing traffic signs. This study has conducted a critical investigation on various machine learning algorithms which gives high accuracy to predict, recognize real-time traffic signs.