Harshal Wangikar, Priya Surana, Prakash Sawant, Napul Labde, A. Shah
{"title":"基于语音警告的实时交通标志识别技术研究进展","authors":"Harshal Wangikar, Priya Surana, Prakash Sawant, Napul Labde, A. Shah","doi":"10.46610/rrmlcc.2022.v01i03.002","DOIUrl":null,"url":null,"abstract":"Road signs are essential for providing information to drivers. Understanding road signs are essential for ensuring traffic safety because doing so can stop 4484 accidents. The identification of traffic signs has been the focus of research in recent decades. Accurate real-time recognition is the cornerstone of a robust but underdeveloped traffic sign recognition system. This study provides drivers with real-time voice-advice traffic sign recognition technology. This system is composed of two subsystems. Using a trained convolutional neural network, the first recognizes and detects traffic signs (CNN). When the system notices a particular traffic sign, the text-to-speech engine is employed to play a voice message to the driver. An efficient- CNN model is built on the reference data set using deep learning methods for search and real-time search. This system's advantage is that it recognizes traffic signs and guides the car even if the driver overlooks, ignores, or doesn't understand them. Say. These technologies are also necessary for the development of autonomous vehicles.","PeriodicalId":149011,"journal":{"name":"Research & Review: Machine Learning and Cloud Computing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Review on Real-Time Traffic Sign Recognition with Voice Warnings\",\"authors\":\"Harshal Wangikar, Priya Surana, Prakash Sawant, Napul Labde, A. Shah\",\"doi\":\"10.46610/rrmlcc.2022.v01i03.002\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Road signs are essential for providing information to drivers. Understanding road signs are essential for ensuring traffic safety because doing so can stop 4484 accidents. The identification of traffic signs has been the focus of research in recent decades. Accurate real-time recognition is the cornerstone of a robust but underdeveloped traffic sign recognition system. This study provides drivers with real-time voice-advice traffic sign recognition technology. This system is composed of two subsystems. Using a trained convolutional neural network, the first recognizes and detects traffic signs (CNN). When the system notices a particular traffic sign, the text-to-speech engine is employed to play a voice message to the driver. An efficient- CNN model is built on the reference data set using deep learning methods for search and real-time search. This system's advantage is that it recognizes traffic signs and guides the car even if the driver overlooks, ignores, or doesn't understand them. Say. These technologies are also necessary for the development of autonomous vehicles.\",\"PeriodicalId\":149011,\"journal\":{\"name\":\"Research & Review: Machine Learning and Cloud Computing\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Research & Review: Machine Learning and Cloud Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46610/rrmlcc.2022.v01i03.002\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Research & Review: Machine Learning and Cloud Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46610/rrmlcc.2022.v01i03.002","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Review on Real-Time Traffic Sign Recognition with Voice Warnings
Road signs are essential for providing information to drivers. Understanding road signs are essential for ensuring traffic safety because doing so can stop 4484 accidents. The identification of traffic signs has been the focus of research in recent decades. Accurate real-time recognition is the cornerstone of a robust but underdeveloped traffic sign recognition system. This study provides drivers with real-time voice-advice traffic sign recognition technology. This system is composed of two subsystems. Using a trained convolutional neural network, the first recognizes and detects traffic signs (CNN). When the system notices a particular traffic sign, the text-to-speech engine is employed to play a voice message to the driver. An efficient- CNN model is built on the reference data set using deep learning methods for search and real-time search. This system's advantage is that it recognizes traffic signs and guides the car even if the driver overlooks, ignores, or doesn't understand them. Say. These technologies are also necessary for the development of autonomous vehicles.