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	Fatigue driving detection model based on multi-feature fusion and semi-supervised active learning
	Li, Xu; Hong, Lin; Wang, Jian-chun; Liu, Xiang
刊名	IET INTELLIGENT TRANSPORT SYSTEMS
	2019
卷号	13期号:9页码:1401-1409
关键词	learning (artificial intelligence) road safety fatigue authors steering features facial features semisupervised active learning algorithm semantic labels rest data efficient fatigue driving detection model unlabelled driving data costly work laborious work novel fatigue
DOI	10.1049/iet-its.2018.5590
URL标识	查看原文
公开日期	[db:dc_date_available]
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/4554607
专题	山东大学
作者单位	1.Shandong Univ Sci & Technol, Coll Transportat, Qingdao 266590, Shandong, Peoples R China. 2.Tongji
推荐引用方式 GB/T 7714	Li, Xu,Hong, Lin,Wang, Jian-chun,et al. Fatigue driving detection model based on multi-feature fusion and semi-supervised active learning[J]. IET INTELLIGENT TRANSPORT SYSTEMS,2019,13(9):1401-1409.
APA	Li, Xu,Hong, Lin,Wang, Jian-chun,&Liu, Xiang.(2019).Fatigue driving detection model based on multi-feature fusion and semi-supervised active learning.IET INTELLIGENT TRANSPORT SYSTEMS,13(9),1401-1409.
MLA	Li, Xu,et al."Fatigue driving detection model based on multi-feature fusion and semi-supervised active learning".IET INTELLIGENT TRANSPORT SYSTEMS 13.9(2019):1401-1409.

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