Recently, multimodal fusion efforts have achieved remarkable success in Multimodal
Sentiment Analysis (MSA). However, most of the existing methods are based on model-level …

Affect recognition in a real-world, less constrained environment is the principal prerequisite
of the industrial-level usefulness of this technology. Monitoring the psychological profile …

In recent years, electroencephalography (EEG) emotion recognition has achieved excellent
progress. However, the applied shallow convolutional neural networks (CNNs) cannot …

Detecting emotions is a growing field aiming to comprehend and interpret human emotions
from various data sources, including text, voice, and physiological signals …

Deep learning techniques have drawn considerable interest in emotion recognition due to
recent technological developments in healthcare analytics. Automatic patient emotion …

Background and objective Background and objective: Human fatigue is a major cause of
road traffic accidents. Currently widely used fatigue driving detection methods are based on …

EEG-based auditory attention decoding (AAD) aims to identify the attended speaker from the
listener's EEG signals. Existing datasets mainly focus on auditory stimuli, ignoring real-world …

The identification of compound fault components of a planetary gearbox is especially
important for kee** the mechanical equipment working safely. However, the recognition …

Emotion recognition holds great promise in healthcare and in the development of affect-
sensitive systems such as brain–computer interfaces (BCIs). However, the high cost of …

In a technologically advanced world, artificial intelligence has impacted all fields of activity.
The augmentation of online learning by means of emotion recognition systems raises new …