Publications (5)
Adaptive Progressive Attention Graph Neural Network for EEG Emotion Recognition
Tianzhi Feng, Chennan Wu, Yi Niu +5
In recent years, numerous neuroscientific studies demonstrate that specific areas of the brain are connected to human emotional responses, with these regions exhibiting variability…
Spatio-Temporal Progressive Attention Model for EEG Classification in Rapid Serial Visual Presentation Task
Yang Li, Wei Liu, Tianzhi Feng +6
As a type of multi-dimensional sequential data, the spatial and temporal dependencies of electroencephalogram (EEG) signals should be further investigated. Thus, in this paper, we…
A Novel Transferability Attention Neural Network Model for EEG Emotion Recognition
Yang Li, Boxun Fu, Fu Li +2
The existed methods for electroencephalograph (EEG) emotion recognition always train the models based on all the EEG samples indistinguishably. However, some of the source (trainin…
Learning from Brain Topography: A Hierarchical Local-Global Graph-Transformer Network for EEG Emotion Recognition
Yijin Zhou, Fu Li, Yi Niu +3
Understanding how local neurophysiological patterns interact with global brain dynamics is essential for decoding human emotions from EEG signals. However, existing deep learning a…
GMSS: Graph-Based Multi-Task Self-Supervised Learning for EEG Emotion Recognition
Yang Li, Ji Chen, Fu Li +7
Previous electroencephalogram (EEG) emotion recognition relies on single-task learning, which may lead to overfitting and learned emotion features lacking generalization. In this p…