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Driver Drowsiness Detection Using Neural Network and Machine Learning Algorithms
Published Online: March-April 2023
Pages: 315-320
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Abstract: The goal of this project is to build a drowsiness detection system that can detect when a person's eyes are closed for a few seconds. The system alerts the driver when drowsiness is detected, because driving when you are drowsy can become very dangerous. Most road accidents are caused by drowsy drivers. So, to prevent these accidents, we will build a system that will alert the driver when he feels drowsy. Our approach to this open problem is to use a series of 60-second images, recorded with the driver's face visible. To determine if a driver is showing symptoms of drowsiness, two alternative solutions have been developed with an emphasis on minimizing false positives. The accuracy achieved by the system is similar: around 60
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