Real-time Driver Drowsiness Detection Using Deep Neural Networks | ||||
International Integrated Intelligent Systems | ||||
Volume 1, Issue 2, June 2024 PDF (629.14 K) | ||||
DOI: 10.21608/iiis.2024.357785 | ||||
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Authors | ||||
Daniel Halim1; Mariam Hanafy1; Youssef Lotfy1; Mohanad Deif2; Rania Elgohary3 | ||||
1Faculty of Engineering Cairo University, Cairo, Egypt | ||||
2Department of Artificial intelligence , College of Information Technology, Misr University for Science & Technology (MUST), 6th of October City 12566 , Egypt | ||||
3Department of Artificial intelligence, College of Information Technology, Misr University for Science & Technology | ||||
Abstract | ||||
This paper presents a driver drowsiness detection for accident prevention which is based on the curvature of the eye. Our attempt is to develop a deep learning model that can use the input from a camera in real time by extracting the eyes to detect the drowsiness of the drivers.This paper helps to resolve the problem of drowsiness detection with an accuracy of 96% for test and 99% for validation | ||||
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