Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue Detection-Reference-Cited by-同舟云学术

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Revolutionizing Road Safety: YOLOv8-Powered Driver Fatigue Detection

Published:2023-12-04 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE)
language:
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Author:

Xie Shuaiyue¹,Chuah Joong Huang²,Chai Grace Mei Ting³

Affiliation:

1. Electronics and Computer Science, University of Southampton,Southampton,United Kingdom,SO17 1BJ

2. University of Malaya,Faculty of Engineering,Department of Electrical Engineering,Kuala Lumpur,Malaysia,50603

3. Smart Manufacturing Systems Research, Group, University of Southampton Malaysia,Iskandar Puteri,Johor,Malaysia,79100

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10487636/10487139/10487765.pdf?arnumber=10487765

Reference16 articles.

1. Can organisational safety climate and occupational stress predict work-related driver fatigue?

2. Research on driver fatigue detection strategy based on human eye state

3. Sensor Applications and Physiological Features in Drivers’ Drowsiness Detection: A Review

4. Evaluation of a Smart Algorithm for Commercial Vehicle Driver Drowsiness Detection

5. A Driving Fatigue Feature Detection Method Based on Multifractal Theory

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Driver distraction and fatigue detection in images using ME‐YOLOv8 algorithm;IET Intelligent Transport Systems;2024-09-02

2. Research on Rapid Recognition of Moving Small Targets by Robotic Arms Based on Attention Mechanisms;Applied Sciences;2024-05-07

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