Real-Time Drowsiness Detection System Using Machine Learning
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-45121-8_5
Reference20 articles.
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2. Deng, W., Wu, R.: Real-time driver-drowsiness detection system using facial features. IEEE Access 7, 118727–118738 (2019)
3. Lin, C.Y., Chang, P., Wang, A., Fan, C.P.: Machine learning and gradient statistics based real-time driver drowsiness detection. In: 2018 IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW), pp. 1–2. IEEE (2018)
4. Sathasivam, S., Saon, S., Sidek, A., Som, M. M., Ameen, H.A.: Drowsiness detection system using eye aspect ratio technique. In: 2020 IEEE Student Conference on Research and Development (SCOReD), pp. 448–452. IEEE (2020)
5. Lecture Notes in Computer Science;S Park,2017
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