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 ...

Artificial intelligence detectors are increasingly used to check the veracity of content online. We ran more than 1,000 tests and found several strengths and plenty of weaknesses. By Stuart A.

Acute sleep deprivation significantly impacts cognitive function, contributes to accidents, and increases the risk of chronic illnesses, underscoring the need for reliable and objective diagnosis. Our ...

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 ...

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 ...

The Real-Time Driver Drowsiness Detection System is an advanced computer vision solution designed to monitor driver alertness and prevent accidents caused by drowsiness. The system analyzes facial ...

In today’s digital background, sentiment analysis has become an essential factor of Natural Language Processing (NLP), offering valuable insights from vast online data sources. This paper presents a ...

This study intends to bring onboard and execute a real-time drowsiness alert system using machine learning that will monitor the drivers' eye movement behaviours, thus, reducing the risk of road ...