421 citations · 569 across the 4 of their papers we have counts for
4 papers
LGGNet: Learning from Local-Global-Graph Representations for Brain-Computer Interface
Yi Ding, Neethu Robinson, Chengxuan Tong +2
Neuropsychological studies suggest that co-operative activities among different brain functional areas drive high-level cognitive processes. To learn the brain activities within an…
TSception: Capturing Temporal Dynamics and Spatial Asymmetry from EEG for Emotion Recognition
Yi Ding, Neethu Robinson, Su Zhang +2
The high temporal resolution and the asymmetric spatial activations are essential attributes of electroencephalogram (EEG) underlying emotional processes in the brain. To learn the…
FBCNet: A Multi-view Convolutional Neural Network for Brain-Computer Interface
Ravikiran Mane, Effie Chew, Karen Chua +5
Lack of adequate training samples and noisy high-dimensional features are key challenges faced by Motor Imagery (MI) decoding algorithms for electroencephalogram (EEG) based Brain-…
TSception: A Deep Learning Framework for Emotion Detection Using EEG
Yi Ding, Neethu Robinson, Qiuhao Zeng +4
In this paper, we propose a deep learning framework, TSception, for emotion detection from electroencephalogram (EEG). TSception consists of temporal and spatial convolutional laye…