3 citations · 3 across the 7 of their papers we have counts for
7 papers
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…
Embedded Multi-label Feature Selection via Orthogonal Regression
Xueyuan Xu, Fulin Wei, Tianyuan Jia +3
In the last decade, embedded multi-label feature selection methods, incorporating the search for feature subsets into model optimization, have attracted considerable attention in a…
Supervised feature selection with orthogonal regression and feature weighting
Xia Wu, Xueyuan Xu, Jianhong Liu +3
Effective features can improve the performance of a model, which can thus help us understand the characteristics and underlying structure of complex data. Previous feature selectio…