Several hypovigilance detection systems (HDx) were developed to avoid road-side
accidents due to driver fatigue. They have suffered from several limitations. Notably many of …

Automatic recognition of the eye states is essential for diverse computer vision applications
related to drowsiness detection, facial emotion recognition (FER), human–computer …

This work presents BlinkLinMulT, a transformer-based framework for eye blink detection.
While most existing approaches rely on frame-wise eye state classification, recent …

Driver drowsiness is a severe problem that usually causes traffic accidents, classified as
more dangerous. The record of the National Safety Council reported that drowsy driving is …

Proper detection of driver drowsiness plays a key role to reduce the accidental rate in our
country. Drowsiness occurs due to slee** during driving. A Convolutional Neural Network …

Traffic accidents always result in great human and material losses. One of the main causes
of accidents is the human factor, which usually results from driver's fatigue or drowsiness. To …

Working in front of the computer for long periods of time leads to exhaustion, fatigue and
high strain on the eyes. Often the natural eye blink activity is disturbed and the eyes do not …

Ocular redness is highly prevalent worldwide and often accompanied by pain, discomfort,
and vision problems, making it an essential signal for monitoring disease development and …

This study focused on the classification of EEG signal. The study aims to make a
classification with fast response and high-performance rate. Thus, it could be possible for …

Deepfakes have been a hot topic in the field of deep learning. It is typically used to alter the
face or body of a person to create a fake image or video. With the rise of internet, the number …