A deep learning-based real-time driver drowsiness detection and alert system using CNN-LSTM architecture. The model analyzes eye movements, mouth openness (yawning), and head pose to accurately ...

A real-time Driver Drowsiness Detection System built using Python, OpenCV, MediaPipe, and Django. The system monitors the driver's eyes through a webcam and detects drowsiness based on eye movement ...

This research addresses the challenge of monitoring railway driver drowsiness using a real-time, vision-based system powered by convolutional neural networks, specifically the YOLOv8 architecture ...

This research presents a Driver Drowsiness Detection System (DDDS) that uses a Convolutional Neural Network (CNN) to improve road safety. The system uses a vast dataset of 97,860 images from the ...

Abstract: Driver fatigue is one of the leading causes of accidents worldwide. One of the most reliable methods of measuring driver fatigue is to detect the driver's drowsiness. Drowsiness and fatigue ...

The objective of this study was to investigate common functional near-infrared spectroscopy (fNIRS) features of mental fatigue induced by different tasks. In addition to distinguishing fatigue from ...