Embedded System for Driver Drowsiness Detection
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3485-0_48
Reference22 articles.
1. N. Neshov and A. Manolova, “Drowsiness monitoring in real-time based on supervised descent method,” 2017 9th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications (IDAACS), 2017, pp. 660–663, doi: https://doi.org/10.1109/IDAACS.2017.8095173.
2. Hong T, Qin H (2007) Drivers drowsiness detection in embedded system. IEEE International Conference on Vehicular Electronics and Safety 2007:1–5. https://doi.org/10.1109/ICVES.2007.4456381
3. Assari MA, Rahmati M (2011) Driver drowsiness detection using face expression recognition. IEEE International Conference on Signal and Image Processing Applications (ICSIPA) 2011:337–341. https://doi.org/10.1109/ICSIPA.2011.6144162
4. Altameem A, Kumar A, Poonia RC, Kumar S, Saudagar AKJ (2021) Early Identification and Detection of Driver Drowsiness by Hybrid Machine Learning. IEEE Access 9:162805–162819. https://doi.org/10.1109/ACCESS.2021.3131601
5. O. Rigane, K. Abbes, C. Abdelmoula and M. Masmoudi, “A Fuzzy Based Method for Driver Drowsiness Detection,” 2017 IEEE/ACS 14th International Conference on Computer Systems and Applications (AICCSA), 2017, pp. 143–147, doi: https://doi.org/10.1109/AICCSA.2017.131.
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