1 Universidad Tecnológica de Lima Sur (UNTELS), Lima, Peru 2 Grupo de Investigación en Computación y Neurociencia Cognitiva, Universidad Tecnológica de Lima Sur (UNTELS), Lima, Peru This research ...

ABSTRACT: 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 ...

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 ...

Design a lightweight machine-learning pipeline that analyzes single-channel frontal EEG data (Fp1/Fp2) and accurately detects driver drowsiness in real-time. 50 Hz IIR notch filter + 0.5–30 Hz ...

Passive sensing via wearable devices and smartphones, combined with machine learning (ML), enables objective, continuous, and noninvasive mental health monitoring. Objective: This study aimed to ...

Abstract: Driver drowsiness causes road accidents as the drowsiness or sleepiness affects the ability of the driver to focus. Drowsiness may happen due to variety of reasons such as lack of sleep, ...

1 Department of Computer Science, College of Computer Engineering and Science, Prince Sattam bin Abdulaziz University, Al Kharj, Saudi Arabia 2 Otto-von-Guericke-University Magdeburg (IIKT), Magdeburg ...

A real-time driver drowsiness detection system using deep learning and computer vision techniques, developed to enhance road safety by identifying signs of driver fatigue through eye state ...

MCED tests utilize liquid biopsies to detect multiple cancer types early, using ctDNA and other biomarkers analyzed by machine learning. Machine learning models, including deep learning, enhance MCED ...

Abstract: Drowsiness is a major source of fatigue, which can endanger the lives of drivers and other passengers. Teachers are confronted every day with students not paying attention in class because ...