Driver Drowsiness Detection based on Multimodal using Fusion of Visual-feature and Bio-signal-Reference-Cited by-同舟云学术

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Driver Drowsiness Detection based on Multimodal using Fusion of Visual-feature and Bio-signal

Published:2018-10 Issue: Volume: Page:
ISSN:
Container-title:2018 International Conference on Information and Communication Technology Convergence (ICTC)
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Author:

Choi Hyung-Tak,Back Moon-Ki,Lee Kyu-Chul

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/8509497/8539346/08539478.pdf?arnumber=8539478

Cited by 18 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

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2. Machine learning-based multimodal fusion recognition of passenger ship seafarers’ workload: A case study of a real navigation experiment;Ocean Engineering;2024-05

3. 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

4. Research on Driving Fatigue Detection Algorithm Based on the eye recognition;Proceedings of the 3rd International Conference on Computer, Artificial Intelligence and Control Engineering;2024-01-26

5. Advanced Intelligent deep learning-based system for Robust Driving Assistance;2023 AEIT International Conference on Electrical and Electronic Technologies for Automotive (AEIT AUTOMOTIVE);2023-07-17

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