5 papers
ProtoGIB-Workload: Learning Workload-Specific Neural Topology Prototypes across Subjects
Yuzhe Zhang, Yixi Zhang, Shengdian Jiang +6
Reliable electroencephalography (EEG)-based mental workload recognition is crucial for adaptive human-centered systems, yet practical deployment requires models to generalize to us…
LibEMER: A novel benchmark and algorithms library for EEG-based Multimodal Emotion Recognition
Zejun Liu, Yunshan Chen, Chengxi Xie +2
EEG-based multimodal emotion recognition(EMER) has gained significant attention and witnessed notable advancements, the inherent complexity of human neural systems has motivated su…
LibEER: A Comprehensive Benchmark and Algorithm Library for EEG-based Emotion Recognition
Huan Liu, Shusen Yang, Yuzhe Zhang +8
EEG-based emotion recognition (EER) has gained significant attention due to its potential for understanding and analyzing human emotions. While recent advancements in deep learning…
MIND-EEG: Multi-granularity Integration Network with Discrete Codebook for EEG-based Emotion Recognition
Yuzhe Zhang, Chengxi Xie, Huan Liu +2
Emotion recognition using electroencephalogram (EEG) signals has broad potential across various domains. EEG signals have ability to capture rich spatial information related to bra…
A Multi-Label EEG Dataset for Mental Attention State Classification in Online Learning
Huan Liu, Yuzhe Zhang, Guanjian Liu +3
Attention is a vital cognitive process in the learning and memory environment, particularly in the context of online learning. Traditional methods for classifying attention states…