As humans, our eyes take in two-dimensional images that our brains convert to three-dimensional experiences. This ability enables us to be aware of our position in space, judge distances, possess ...
Machine learning models that use electronic health record data to predict obstructive sleep apnea had greater performance than two screening questionnaires, according to a poster presented at SLEEP ...
Accurate RNA splicing is essential for gene expression and human health, yet predicting how DNA sequence variations affect ...
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.
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 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 ...
Abstract: The face, an essential part of the body, communicates a vast array of information. When a driver is fatigued, their facial expressions, along with the frequency of blinking and yawning, ...
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