Automatic Driver Drowsiness Detection Using Artificial Neural Network Based on Visual Facial Descriptors: Pilot Study-Reference-Cited by-同舟云学术

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Automatic Driver Drowsiness Detection Using Artificial Neural Network Based on Visual Facial Descriptors: Pilot Study

Published:2022-09 Issue: Volume:Volume 14 Page:1641-1649
ISSN:1179-1608
Container-title:Nature and Science of Sleep
language:en
Short-container-title:NSS

Author:

Inkeaw Papangkorn,Srikummoon Pimwarat,Chaijaruwanich Jeerayut,Traisathit Patrinee,Awiphan Suphakit^ORCID,Inchai Juthamas^ORCID,Worasuthaneewan Ratirat,Theerakittikul Theerakorn^ORCID

Publisher

Informa UK Limited

Subject

Behavioral Neuroscience,Applied Psychology

Reference55 articles.

1. World Health Organization. Review of Thailand’s status against voluntary global targets for road safety risk factors and service delivery mechanism; 2020.

2. Central Information Technology Center. Road crash case statistics. Available from: www.pitc.police.go.th//2014. Accessed October 19, 2014.

3. World Health Organization. Global status report on road safety 2015; 2015. Available from: http://www.who.int/violence_injury_prevention/road_safety_status/20.15/en/ Accessed September 7, 2022.

4. Identification of Factors Affecting Road Traffic Injuries Incidence and Severity in Southern Thailand Based on Accident Investigation Reports

Cited by 1 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. Drowsy Alert: A System to Detect and Alert Driver's Drowsiness for Road Safety;2024 IEEE Students Conference on Engineering and Systems (SCES);2024-06-21

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