11 citations · 11 across the 1 of their papers we have counts for
4 papers
Investigating EEG-Based Functional Connectivity Patterns for Multimodal Emotion Recognition
Xun Wu, Wei-Long Zheng, Bao-Liang Lu
Compared with the rich studies on the motor brain-computer interface (BCI), the recently emerging affective BCI presents distinct challenges since the brain functional connectivity…
Multimodal Emotion Recognition Using Deep Canonical Correlation Analysis
Wei Liu, Jie-Lin Qiu, Wei-Long Zheng +1
Multimodal signals are more powerful than unimodal data for emotion recognition since they can represent emotions more comprehensively. In this paper, we introduce deep canonical c…
Semi-supervised Deep Generative Modelling of Incomplete Multi-Modality Emotional Data
Changde Du, Changying Du, Hao Wang +4
There are threefold challenges in emotion recognition. First, it is difficult to recognize human's emotional states only considering a single modality. Second, it is expensive to m…
Multimodal Emotion Recognition Using Multimodal Deep Learning
Wei Liu, Wei-Long Zheng, Bao-Liang Lu
To enhance the performance of affective models and reduce the cost of acquiring physiological signals for real-world applications, we adopt multimodal deep learning approach to con…