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 ...

A recent study "Real-time anti-sleep alert algorithm to prevent road accidents to ensure road safety" introduces a real-time anti-sleep alert system, leveraging deep learning ... driver behavior ...

Using the APTOS 2019 Blindness Detection dataset, which includes diverse, labeled retinal images, we train, test, and benchmark deep learning models under standardized conditions, employing Python and ...

most deep learning models lack interpretability due to their black-box nature. To address these issues, we propose a novel interpretable residual shrinkage network, namely, ID3RSNet, for cross-subject ...

Using the data ... Progressive drowsy detection empowers managers to intervene effectively. Advanced drowsy driving detection offers early warnings to drivers, enabling them to take immediate ...

Drowsiness Detection uses Samsara ... has seen a significant decrease in how often drivers fall asleep during shifts since using its Drowsiness Detection. According to their VP of health ...

The company’s Drowsiness Detection feature uses its AI Dash Cams to monitor factors, such as eye movement and yawning, and then alerts drivers when they are dangerously fatigued. The new ...

This system promotes safer public transportation and enhances professionalism by monitoring driver alertness. The system detects closed eyes and performs a cross-reference using personalization data ...

300+ innovations will shape the automotive industry According to GlobalData’s Technology Foresights, which plots the S-curve for the automotive industry using innovation intensity models built ...