Driver Drowsiness Alert System Using Real-Time Detection-Reference-Cited by-同舟云学术

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Driver Drowsiness Alert System Using Real-Time Detection

Published:2022 Issue: Volume: Page:65-81
ISSN:1860-949X
Container-title:AI and IoT for Smart City Applications
language:
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Author:

Mridha Krishna,Shaw Rabindra Nath,Kumar Dinesh,Ghosh Ankush

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-7498-3_5

Reference36 articles.

1. Taylor C (2020) Drowsy driving statistics. https://www.thezebra.com/chapter/drowsy-driving-statistics/

2. NSF (2020) Warning Signs. https://drowsydriving.org/about/warningsigns/

3. Wang T, Shi P (2005) Yawning detection for determining driver drowsiness. In: Proceedings of IEEE international workshop

4. Lu Y, Wang Z (2007) Detecting driver yawning in successive images. In: 1st International conference on bioinformatics and biomedical engineering

5. Anizy GJ, Nordin MJ, Razooq MM (2015) Automatic driver drowsiness detection using Haar algorithm and support vector machine techniques. Asian J Appl Sci Papers 8(2):149–157

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. Real time image processing monitoring system based IoT;AIP Conference Proceedings;2023

2. ML-MT: A Study of e-Health Application Framework by Machine Learning Techniques;2022 IEEE 4th International Conference on Cybernetics, Cognition and Machine Learning Applications (ICCCMLA);2022-10-08

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