使用机器学习检测交通规则违规:分析综述

Kaushik Biswas, N. Paul, Dipanwita Saha, Tanvir Ahmed, Rifath Mahmud
{"title":"使用机器学习检测交通规则违规:分析综述","authors":"Kaushik Biswas, N. Paul, Dipanwita Saha, Tanvir Ahmed, Rifath Mahmud","doi":"10.56532/mjsat.v3i1.146","DOIUrl":null,"url":null,"abstract":"This research paper focuses on current and previous efforts to detect traffic rule violations. So far, some remarkable works have been discovered, and many approaches for detecting traffic rule violations have been introduced from the current situation. Hence, machine learning has been the main target to detect traffic rule violations. A summary of the frameworks and methods that have been used to solve this problem so far is also provided in this study. This study has been divided into two parts. In the first part, the recent works on traffic rule violations have been portrayed. Moreover, the algorithms and frameworks that have been used so far and major works on violation detection using machine learning can be found in this section. In the second part, this study summarizes a brief discussion based on the image quality, camera resolution, device performance, and accuracy level of the works, as well as the algorithms and frameworks that have been used to conduct the detection of traffic rule violation problems using machine learning.","PeriodicalId":407405,"journal":{"name":"Malaysian Journal of Science and Advanced Technology","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Detection of Traffic Rule Violations Using Machine Learning: An Analytical Review\",\"authors\":\"Kaushik Biswas, N. Paul, Dipanwita Saha, Tanvir Ahmed, Rifath Mahmud\",\"doi\":\"10.56532/mjsat.v3i1.146\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This research paper focuses on current and previous efforts to detect traffic rule violations. So far, some remarkable works have been discovered, and many approaches for detecting traffic rule violations have been introduced from the current situation. Hence, machine learning has been the main target to detect traffic rule violations. A summary of the frameworks and methods that have been used to solve this problem so far is also provided in this study. This study has been divided into two parts. In the first part, the recent works on traffic rule violations have been portrayed. Moreover, the algorithms and frameworks that have been used so far and major works on violation detection using machine learning can be found in this section. In the second part, this study summarizes a brief discussion based on the image quality, camera resolution, device performance, and accuracy level of the works, as well as the algorithms and frameworks that have been used to conduct the detection of traffic rule violation problems using machine learning.\",\"PeriodicalId\":407405,\"journal\":{\"name\":\"Malaysian Journal of Science and Advanced Technology\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Malaysian Journal of Science and Advanced Technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.56532/mjsat.v3i1.146\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Malaysian Journal of Science and Advanced Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.56532/mjsat.v3i1.146","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

这篇研究论文的重点是当前和以前在检测交通规则违规方面的努力。到目前为止,已经发现了一些值得注意的工作,并从目前的情况介绍了许多检测交通违规的方法。因此,机器学习一直是检测交通规则违规的主要目标。本研究还总结了迄今为止用于解决这一问题的框架和方法。本研究分为两部分。第一部分,对近年来的交通违章工作进行了描述。此外,到目前为止使用的算法和框架以及使用机器学习进行违规检测的主要工作可以在本节中找到。在第二部分中,本研究总结了基于作品的图像质量、相机分辨率、设备性能和精度水平的简要讨论,以及用于使用机器学习进行交通规则违规问题检测的算法和框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection of Traffic Rule Violations Using Machine Learning: An Analytical Review
This research paper focuses on current and previous efforts to detect traffic rule violations. So far, some remarkable works have been discovered, and many approaches for detecting traffic rule violations have been introduced from the current situation. Hence, machine learning has been the main target to detect traffic rule violations. A summary of the frameworks and methods that have been used to solve this problem so far is also provided in this study. This study has been divided into two parts. In the first part, the recent works on traffic rule violations have been portrayed. Moreover, the algorithms and frameworks that have been used so far and major works on violation detection using machine learning can be found in this section. In the second part, this study summarizes a brief discussion based on the image quality, camera resolution, device performance, and accuracy level of the works, as well as the algorithms and frameworks that have been used to conduct the detection of traffic rule violation problems using machine learning.
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
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信