Driver Drowsiness Detection System Using Machine Learning Technique
Author:
Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56700-1_2
Reference20 articles.
1. Chacon-Murguia, M.I., Prieto-Resendiz, C.: Detecting driver drowsiness: a survey of system designs and technology. IEEE Consum. Electron. Mag 4(4), 107–119 (2015)
2. Nordbakke, S., Sagberg, F.: Sleepy at the wheel: Knowledge, symptoms and behaviour among car drivers. Res. Gate 1–10 (2007). ISSN 1369-8478
3. de Naurois, C.J., Bourdin, C., Stratulat, A., Diaz, E., Vercher, J.L.: Detection and prediction of driver drowsiness using artificial neural network models. Accid. Anal. Prev. 126, 95–104 (2019)
4. Arefnezhad, S., Hamet, J., Eichberger, A., et al.: Driver drowsiness estimation using EEG signals with a dynamical encoder–decoder modeling framework. Sci. Rep. 12, 2650 (2022)
5. Arefnezhad, S., Samiee, S., Eichberger, A., Nahvi, A.: Driver drowsiness detection based on steering wheel data applying adaptive neuro-fuzzy feature selection. Sensors 19(4), 943 (2019)
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