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:1-6
ISSN:
Container-title:2023 International Conference on Sustainable Technology and Engineering (i-COSTE)
language:
Short-container-title:

Author:

Xie Shuaiyue¹,Chuah Joong Huang²,Ting Chai Grace Mei³

Affiliation:

1. University of Southampton,Electronics and Computer Science,Southampton,United Kingdom,SO171BJ

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

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

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10500762/10500763/10500771.pdf?arnumber=10500771

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

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