Electroencephalograms (EEG)-based technology for recognizing emotions has attracted a
lot of interest lately. However, there is still work to be done on the efficient fusion of different …

In real-world scenarios, the facial expression recognition task faces several challenges,
including lighting variations, image noise, face occlusion, and other factors, which limit the …

Driver distraction detection not only helps to improve road safety and prevent traffic
accidents, but also promotes the development of intelligent transportation systems, which is …

Driver state is critical for safety in mixed traffic environments with automated and human-
driven vehicles. Recognizing and monitoring the driver's state is essential to provide early …

Rear-end collisions, mainly resulting from driver's braking errors due to hazard
misrecognition, significantly contribute to traffic accidents. A topic of popular concern …

Recently, there has been an increasing interest in the effects of stress and negative
emotions on driving performance and road safety. As a consequence, there is a growing …

Objective Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas.
Despite existing studies on deep learning models for LC identification, challenges remain in …

Though driving automation promises to improve driving safety, drivers are still required to be
ready to retake control in conditionally automated vehicles, which are defined by the Society …

Facial expression recognition (FER) has become a prominent research area due to its wide
range of applications, such as human-robot interaction (HRI), driver state monitoring, and …

A practical facial expression recognition system should be person-independent and robust
against factors such as noise and resolution. This paper handles these issues and offers a …