most citedJoint Contrastive Learning with Feature Alignment for Cross-Corpus EEG-based Emotion Recognition

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026

Brain-Token Learning: Microstate-Based Tokenization and Multi-Scale Interaction for Long-Horizon EEG Sequence Modeling

Weishan Ye, Yue Pan, Li Zhang +2

Electroencephalography (EEG) provides a non-invasive window into dynamic brain activity, yet modeling long-horizon EEG sequences remains challenging due to their high temporal comp…

cs.HC2026

EEGDancer: Dynamic Emotion Latent Space Masked Modeling with Reinforcement Learning for EEG Continuous Emotion Prediction

Zhihao Zhou, Weishan Ye, Li Zhang +2

Continuous electroencephalography (EEG) emotion prediction aims to model the temporal evolution of human emotional states from EEG signals. Unlike conventional discrete emotion rec…

cs.LG2024

NSSI-Net: A Multi-Concept GAN for Non-Suicidal Self-Injury Detection Using High-Dimensional EEG in a Semi-Supervised Framework

Zhen Liang, Weishan Ye, Qile Liu +3

Non-suicidal self-injury (NSSI) is a serious threat to the physical and mental health of adolescents, significantly increasing the risk of suicide and attracting widespread public…

cs.HC2024

Emotion-Agent: Unsupervised Deep Reinforcement Learning with Distribution-Prototype Reward for Continuous Emotional EEG Analysis

Zhihao Zhou, Qile Liu, Jiyuan Wang +1

Continuous electroencephalography (EEG) signals are widely used in affective brain-computer interface (aBCI) applications. However, not all continuously collected EEG signals are r…

cs.HC2024

EEG-SCMM: Soft Contrastive Masked Modeling for Cross-Corpus EEG-Based Emotion Recognition

Qile Liu, Weishan Ye, Lingli Zhang +1

Emotion recognition using electroencephalography (EEG) signals has attracted increasing attention in recent years. However, existing methods often lack generalization in cross-corp…

cs.HC2024★ 1 cited

Joint Contrastive Learning with Feature Alignment for Cross-Corpus EEG-based Emotion Recognition

Qile Liu, Zhihao Zhou, Jiyuan Wang +1

The integration of human emotions into multimedia applications shows great potential for enriching user experiences and enhancing engagement across various digital platforms. Unlik…