Emotions are a critical aspect of daily life and serve a crucial role in human decision-making,
planning, reasoning, and other mental states. As a result, they are considered a significant …

Emotion recognition technology through analyzing the EEG signal is currently an essential
concept in Artificial Intelligence and holds great potential in emotional health care, human …

Electroencephalography (EEG) measures the neuronal activities in different brain regions
via electrodes. Many existing studies on EEG-based emotion recognition do not fully exploit …

EEG signals have been reported to be informative and reliable for emotion recognition in
recent years. However, the inter-subject variability of emotion-related EEG signals still poses …

Even with an unprecedented breakthrough of deep learning in electroencephalography
(EEG), collecting adequate labelled samples is a critical problem due to laborious and time …

Previous electroencephalogram (EEG) emotion recognition relies on single-task learning,
which may lead to overfitting and learned emotion features lacking generalization. In this …

Emotion recognition based on electroencephalography (EEG) is of great important in the
field of Human–Computer Interaction (HCI), which has received extensive attention in recent …

EEG-based emotion recognition has become an important task in affective computing and
intelligent interaction. However, how to effectively combine the spatial, spectral, and …

Interpreting and labeling human electroencephalogram (EEG) is a challenging task
requiring years of medical training. We present a framework for learning representations …

The dynamic uncertain relationship among each brain region is a necessary factor that limits
EEG-based emotion recognition. It is a thought-provoking problem to availably employ time …