6 citations · 12 across the 9 of their papers we have counts for
9 papers
Physiological Prior-Driven Label Enhancement for Cross-Subject EEG Emotion Recognition
Hongyu Zhu, Lin Chen, Yuming Fu +2
Electroencephalography (EEG)-based emotion recognition captures affective neural signals with high temporal precision, but cross-subject variability and label noise remain critical…
BiMoE: Brain-Inspired Experts for EEG-Dominant Affective State Recognition
Hongyu Zhu, Lin Chen, Mingsheng Shang
Multimodal Sentiment Analysis (MSA) that integrates Electroencephalogram (EEG) with peripheral physiological signals (PPS) is crucial for the development of brain-computer interfac…
MS-Mix: Sentiment-Guided Adaptive Augmentation for Multimodal Sentiment Analysis
Hongyu Zhu, Lin Chen, Xin Jin +1
Multimodal Sentiment Analysis (MSA) integrates complementary features from text, video, and audio for robust emotion understanding in human interactions. However, models suffer fro…
Relax DARTS: Relaxing the Constraints of Differentiable Architecture Search for Eye Movement Recognition
Hongyu Zhu, Xin Jin, Hongchao Liao +3
Eye movement biometrics is a secure and innovative identification method. Deep learning methods have shown good performance, but their network architecture relies on manual design…
EM-DARTS: Hierarchical Differentiable Architecture Search for Eye Movement Recognition
Huafeng Qin, Hongyu Zhu, Xin Jin +3
Eye movement biometrics has received increasing attention thanks to its highly secure identification. Although deep learning (DL) models have shown success in eye movement recognit…
A Survey on Mixup Augmentations and Beyond
Xin Jin, Hongyu Zhu, Siyuan Li +6
As Deep Neural Networks have achieved thrilling breakthroughs in the past decade, data augmentations have garnered increasing attention as regularization techniques when massive la…