Emotion recognition based on electroencephalography (EEG) is a significant task in the
brain-computer interface field. Recently, many deep learning-based emotion recognition …

Automatic emotion recognition based on electroencephalogram (EEG) has attracted rapidly
increasing interests. Due to large inter-subject variabilities, subject-independent emotion …

Electroencephalograph (EEG) emotion recognition is a significant task in the brain-computer
interface field. Although many deep learning methods are proposed recently, it is still …

Automatic electroencephalogram (EEG) emotion recognition is a challenging component of
human–computer interaction (HCI). Inspired by the powerful feature learning ability of …

Human emotion recognition could greatly contribute to human–computer interaction with
promising applications in artificial intelligence. One of the challenges in recognition tasks is …

Deep learning (DL) technologies have recently shown great potential in emotion recognition
based on electroencephalography (EEG). However, existing DL-based EEG emotion …

Recently, the combination of neural network and attention mechanism is widely employed
for electroencephalogram (EEG) emotion recognition (EER) and has achieved remarkable …

In this paper, we present a novel method, called four-dimensional convolutional recurrent
neural network, which integrating frequency, spatial and temporal information of …

Emotion recognition based on electroencephalography (EEG) has attracted significant
attention due to its wide range of applications, especially in Human-Computer Interaction …

Convolutional neural networks (CNNs) have achieved better performance than traditional
algorithms in electroencephalogram (EEG)-based emotion recognition tasks in recent years …