All the existing deep learning solutions for drowsiness detection are computationally intensive and cannot be easily implemented on embedded devices. In this paper, we propose a real-time driver drowsiness detection solution implemented on a smartphone. The proposed solution makes use of a ...
In this paper, a novel approach towards real-time drowsiness detection is proposed. This approach is based on a deep learning method that can be implemented on Android applications with high accuracy. The main contribution of this work is the compression of heavy baseline model to a lightweight...
This paper presents a study in which driver's gaze zone is categorized using new deep learning techniques. Since the sequence of gaze zones of a driver ref... IH Choi,SK Hong,YG Kim - IEEE 被引量: 12发表: 2016年 Real-Time Driver Drowsiness Detection for Embedded System Using Model Compr...
Conclusions: Using the proposed algorithm, it is possible to identify driver anomalies and provide new ideas for the development of intelligent vehicles. 展开 关键词: mixed learning model drowsiness detection ECG heart rate variability DOI: 10.1515/bmt-2023-0193 年份: 2024 ...
Deep learning is an alternative solution which provides a better performance by learning features automatically. Thus, this paper proposed a new concept for handling the real-time driver drowsiness detection using the hybrid of convolutional neural network (CNN) and long short-term memory (LSTM). ...
ECG signals were pre-processed using a 0.5 Hz high-pass butterworth filter (order = 5), followed by powerline filtering (powerline = 50). The peak detection algorithm employed by the Neurokit2 method is based on QRS complex detection using the absolute gradient of the ECG signal (Brammer, ...
Driver drowsiness detection is a car safety Technology which helps prevent accidents caused by the driver getting drowsy. The following code uses computer vision to observe the driver's face, either using a built-in cameraor on mobile devices. ...
I’m not sure when I’ll be releasing the Raspberry Pi version of the tutorial — most of my time lately has been spent writing Deep Learning for Computer Vision with Python. As for using Haar cascades for face detection, be sure to take a look at Practical Python and OpenCV where I ...
Driver drowsiness detection3D convolution neural networkState probability vectorTransfer learningResidual learningDriver drowsiness is a major cause of road accidents. In this study, a novel approach that detects human drowsiness is proposed and investigated. First, driver face and facial landmarks are ...
This is a project implementing Computer Vision and Deep Learning concepts to detect drowsiness of a driver and sound an alarm if drowsy. Youtube Demo :https://youtu.be/3uMlNuXfNfc • Built a model for drowsiness detection of a driver by real-time Eye-Tracking in videos using Haar Cascade...