The final, formatted version of the article will be published soon. Driver drowsiness is a serious concern for road safety within intelligent transportation systems and it can reduce the safety and ...
Researchers at Trinity College Dublin have found that a machine learning model could help clinicians predict which people with depression are more likely to improve with digital cognitive behavioral ...
Using a single 3D deep learning model, researchers from Edith Cowan University (ECU) are able to detect three major causes of road accidents simultaneously – blood alcohol concentration, fatigue and ...
Researchers from Edith Cowan University (ECU) are developing new technology that could change how drunk and dangerous drivers ...
Abstract: Driver drowsiness is a significant cause of road accidents, making early detection essential for improving traffic safety. This paper proposes a vision-based software system for detecting ...
Abstract: This work deals with the fabrication and validation of an innovative wearable single-channel electroencephalogram (EEG) system, designed for real-time monitoring of specific brain activity.
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 ...
Either way, let’s not be in denial about it. Credit...Illustration by Christoph Niemann Supported by By Kevin Roose and Casey Newton Kevin Roose and Casey Newton are the hosts of The Times’s “Hard ...
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