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 ...

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 ...

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 ...

Abstract: Utilizing eye aspect ratio analysis and facial landmarks, the sleep detection tool is intended to detect indicators of sleepiness or drowsiness in people. By leveraging the face recognition ...

The ability to catch a blink of an eye, detect the pupil, and even track its movements may seem like fancy tasks, but they have numerous practical applications. Let’s explore a handful of use cases ...

The fatality of road accidents in this era is alarming. According to WHO, approximately 1.30 million people die each year in road accidents. Road accidents result in significant socioeconomic losses ...

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 ...