Driver drowsiness detection using ANN image processing

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Abstract

The paper presents a study regarding the possibility to develop a drowsiness detection system for car drivers based on three types of methods: EEG and EOG signal processing and driver image analysis. In previous works the authors have described the researches on the first two methods. In this paper the authors have studied the possibility to detect the drowsy or alert state of the driver based on the images taken during driving and by analyzing the state of the driver's eyes: opened, half-opened and closed. For this purpose two kinds of artificial neural networks were employed: a 1 hidden layer network and an autoencoder network.

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Vesselenyi, T., Moca, S., Rus, A., Mitran, T., & Tǎtaru, B. (2017). Driver drowsiness detection using ANN image processing. In IOP Conference Series: Materials Science and Engineering (Vol. 252). Institute of Physics Publishing. https://doi.org/10.1088/1757-899X/252/1/012097

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