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Real time driver drowsiness detection using a logistic-regression-based machine learning algorithm

机译:使用基于Logistic回归的机器学习算法实时检测驾驶员的睡意

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The number of car accidents due to driver drowsiness is very steep. An automated non-contact system that can detect driver's drowsiness early could be lifesaving. Motivated by this dire need, we propose a novel method that can detect driver's drowsiness at an early stage by computing heart rate variation using advanced logistic regression based machine learning algorithm. Our developed technique has been tested with human subjects and it can detect drowsiness in a minimum amount of time, with an accuracy above 90%.
机译:由于驾驶员困倦而导致的车祸数量非常陡峭。可以及早发现驾驶员困倦的自动化非接触式系统可以挽救生命。基于这种迫切的需求,我们提出了一种新颖的方法,该方法可以通过使用基于高级逻辑回归的机器学习算法来计算心率变化,从而在早期阶段检测驾驶员的睡意。我们开发的技术已经在人类受试者身上进行了测试,并且可以在最短的时间内检测到睡意,其准确率超过90%。

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