Driver Drowsiness Detection using Convoluted Neural Networks

Nihal Antony, Rohit Kr, Shreya Patel, S. S, Namratha M
{"title":"Driver Drowsiness Detection using Convoluted Neural Networks","authors":"Nihal Antony, Rohit Kr, Shreya Patel, S. S, Namratha M","doi":"10.1109/ICATIECE45860.2019.9063837","DOIUrl":null,"url":null,"abstract":"Driver drowsiness is one of the leading causes of accidents among motorists today, therefore it is recognized as a serious problem that needs to be resolved. Although there have been many methods proposed in the past to tackle this issue, computer vision seems to be the most promising tool to detect driver drowsiness. Previous works have focused on particular features of the driver’s face and made used of handcrafted algorithms to detect drowsiness in an individual, this paper, however, aims to make use of a convoluted neural network to determine how features of the face give an indication of driver drowsiness.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICATIECE45860.2019.9063837","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

Driver drowsiness is one of the leading causes of accidents among motorists today, therefore it is recognized as a serious problem that needs to be resolved. Although there have been many methods proposed in the past to tackle this issue, computer vision seems to be the most promising tool to detect driver drowsiness. Previous works have focused on particular features of the driver’s face and made used of handcrafted algorithms to detect drowsiness in an individual, this paper, however, aims to make use of a convoluted neural network to determine how features of the face give an indication of driver drowsiness.
基于卷积神经网络的驾驶员困倦检测
司机困倦是当今司机发生事故的主要原因之一,因此,这是一个需要解决的严重问题。尽管过去已经提出了许多方法来解决这个问题,但计算机视觉似乎是最有前途的检测司机困倦的工具。以前的工作集中在驾驶员面部的特定特征上,并使用手工制作的算法来检测个人的睡意,然而,本文旨在利用卷积神经网络来确定面部特征如何指示驾驶员的睡意。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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:481959085
Book学术官方微信