People's emotions play an important part in our daily life and can not only reflect
psychological and physical states, but also play a vital role in people's communication …

With the development of affective computing, discriminative feature selection is critical for
electroencephalography (EEG) emotion recognition. In this article, we fused four EEG …

Emotion recognition based on electroencephalography (EEG) has attracted significant
attention and achieved considerable advances in the fields of affective computing and …

The use of EEG for evaluating and diagnosing neurological abnormalities related to
psychiatric diseases and identifying human emotions has been improved by deep learning …

Emotion Recognition through electroencephalography (EEG) is one of the prevailing
emotion recognition techniques achieving higher accuracy rates. Nevertheless, one of the …

Abstract Temporal Convolutional Networks (TCNs) expand their receptive field through
dilated convolutions, which is essential for capturing dependencies in longer sequences …

Despite promising results reported in the literature for mental workload assessment using
electroencephalography (EEG), most of the proposed methods rely on employing multiple …

Faced with the growing renewable energy requirements, there is increased interest in cross-
region of large-scale renewable energy market, which provides an alternative path for …

Emotional intelligence (EI), a critical aspect of regulating emotions and behavior in daily life,
holds paramount significance in both psychology research and real-world applications …