7 papers
Toward High-Fidelity Visual Reconstruction: From EEG-Based Conditioned Generation to Joint-Modal Guided Rebuilding
Zhijian Gong, Tianren Yao, Wenjia Dong +1
Human visual reconstruction aims to reconstruct fine-grained visual stimuli based on subject-provided descriptions and corresponding neural signals. As a widely adopted modality, E…
Incomplete Depression Feature Selection with Missing EEG Channels
Zhijian Gong, Wenjia Dong, Xueyuan Xu +3
As a critical mental health disorder, depression has severe effects on both human physical and mental well-being. Recent developments in EEG-based depression analysis have shown pr…
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 emotional tagging
Tianze Yu, Junming Zhang, Wenjia Dong +2
EEG based multi-dimension emotion recognition has attracted substantial research interest in human computer interfaces. However, the high dimensionality of EEG features, coupled wi…