3 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
FDC-Net: Rethinking the association between EEG artifact removal and multi-dimensional affective computing
Wenjia Dong, Xueyuan Xu, Tianze Yu +2
Electroencephalogram (EEG)-based emotion recognition holds significant value in affective computing and brain-computer interfaces. However, in practical applications, EEG recording…
ASLSL: Adaptive shared latent structure learning with incomplete multi-modal physiological data for multi-dimensional emotional feature selection
Xueyuan Xu, Tianze Yu, Wenjia Dong +2
Recently, multi-modal physiological signals based emotion recognition has garnered increasing attention in the field of brain-computer interfaces. Nevertheness, the associated mult…
REFS: Robust EEG feature selection with missing multi-dimensional annotation for emotion recognition
Xueyuan Xu, Wenjia Dong, Fulin Wei +1
The affective brain-computer interface is a crucial technology for affective interaction and emotional intelligence, emerging as a significant area of research in the human-compute…
ADSEL: Adaptive Dual Self-Expression Learning for EEG Feature Selection via Incomplete Multi-Dimensional Emotion Labels
Tianze Yu, Junming Zhang, Wenjia Dong +4
EEG based multi-dimension emotion recognition has attracted substantial research interest in affective computing. However, the high dimensionality of EEG features, coupled with lim…
CWEFS: Brain volume conduction effects inspired channel-wise EEG feature selection for multi-dimensional emotion recognition
Xueyuan Xu, Wenjia Dong, Fulin Wei +1
Due to the intracranial volume conduction effects, high-dimensional multi-channel electroencephalography (EEG) features often contain substantial redundant and irrelevant informati…