Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm-Reference-Cited by-同舟云学术

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Driver Drowsiness Classification Based on Eye Blink and Head Movement Features Using the k-NN Algorithm

Published:2020-12-01 Issue: Volume: Page:
ISSN:
Container-title:2020 IEEE Symposium Series on Computational Intelligence (SSCI)
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Author:

Dreisig Mariella,Baccour Mohamed Hedi,Schack Tim,Kasneci Enkelejda

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9308061/9308107/09308133.pdf?arnumber=9308133

Cited by 21 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. Safety Aspects of In-Vehicle Infotainment Systems: A Systematic Literature Review from 2012 to 2023;Electronics;2024-06-29

2. Intelligent learners distraction and drowsiness prediction through EEG signal and iris angel position with brain vision algorithm;Journal of Intelligent & Fuzzy Systems;2024-04-09

3. Comparative Study of Yawn Classification on CNN Architectures;2024 IEEE International Conference on Artificial Intelligence and Mechatronics Systems (AIMS);2024-02-21

4. A Dynamic Head Gesture Recognition Method for Real-time Intention Inference and Its Application to Visual Human-robot Interaction;International Journal of Control, Automation and Systems;2024-01

5. A Deep Learning Model Based On Multi-granularity Facial Features And LSTM Network For Driver Drowsiness Detection;J APPL SCI ENG;2024

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