11 citations · 37 across the 14 of their papers we have counts for
15 papers
PTSM: Physiology-aware and Task-invariant Spatio-temporal Modeling for Cross-Subject EEG Decoding
Changhong Jing, Yan Liu, Shuqiang Wang +5
Cross-subject electroencephalography (EEG) decoding remains a fundamental challenge in brain-computer interface (BCI) research due to substantial inter-subject variability and the…
Generative AI Enables EEG Super-Resolution via Spatio-Temporal Adaptive Diffusion Learning
Shuqiang Wang, Tong Zhou, Yanyan Shen +3
Electroencephalogram (EEG) technology, particularly high-density EEG (HD EEG) devices, is widely used in fields such as neuroscience. HD EEG devices improve the spatial resolution…
Multi-modal Mood Reader: Pre-trained Model Empowers Cross-Subject Emotion Recognition
Yihang Dong, Xuhang Chen, Yanyan Shen +3
Emotion recognition based on Electroencephalography (EEG) has gained significant attention and diversified development in fields such as neural signal processing and affective comp…
BDHT: Generative AI Enables Causality Analysis for Mild Cognitive Impairment
Qiankun Zuo, Ling Chen, Yanyan Shen +3
Effective connectivity estimation plays a crucial role in understanding the interactions and information flow between different brain regions. However, the functional time series u…
Dynamic Community Detection via Adversarial Temporal Graph Representation Learning
Changwei Gong, Changhong Jing, Yanyan Shen +1
Dynamic community detection has been prospered as a powerful tool for quantifying changes in dynamic brain network connectivity patterns by identifying strongly connected sets of n…
Morphological feature visualization of Alzheimer's disease via Multidirectional Perception GAN
Wen Yu, Baiying Lei, Yanyan Shen +5
The diagnosis of early stages of Alzheimer's disease (AD) is essential for timely treatment to slow further deterioration. Visualizing the morphological features for the early stag…
A Prior Guided Adversarial Representation Learning and Hypergraph Perceptual Network for Predicting Abnormal Connections of Alzheimer's Disease
Qiankun Zuo, Baiying Lei, Shuqiang Wang +3
Alzheimer's disease is characterized by alterations of the brain's structural and functional connectivity during its progressive degenerative processes. Existing auxiliary diagnost…
DecGAN: Decoupling Generative Adversarial Network detecting abnormal neural circuits for Alzheimer's disease
Junren Pan, Baiying Lei, Shuqiang Wang +3
One of the main reasons for Alzheimer's disease (AD) is the disorder of some neural circuits. Existing methods for AD prediction have achieved great success, however, detecting abn…
Characterization Multimodal Connectivity of Brain Network by Hypergraph GAN for Alzheimer's Disease Analysis
Junren Pan, Baiying Lei, Yanyan Shen +3
Using multimodal neuroimaging data to characterize brain network is currently an advanced technique for Alzheimer's disease(AD) Analysis. Over recent years the neuroimaging communi…
Multimodal Representations Learning and Adversarial Hypergraph Fusion for Early Alzheimer's Disease Prediction
Qiankun Zuo, Baiying Lei, Yanyan Shen +3
Multimodal neuroimage can provide complementary information about the dementia, but small size of complete multimodal data limits the ability in representation learning. Moreover,…
A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction
Bowen Hu, Baiying Lei, Yanyan Shen +2
Fusing medical images and the corresponding 3D shape representation can provide complementary information and microstructure details to improve the operational performance and accu…
Bidirectional Mapping Generative Adversarial Networks for Brain MR to PET Synthesis
Shengye Hu, Baiying Lei, Yong Wang +3
Fusing multi-modality medical images, such as MR and PET, can provide various anatomical or functional information about human body. But PET data is always unavailable due to diffe…
Tensorizing GAN with High-Order Pooling for Alzheimer's Disease Assessment
Wen Yu, Baiying Lei, Michael K. Ng +3
It is of great significance to apply deep learning for the early diagnosis of Alzheimer's Disease (AD). In this work, a novel tensorizing GAN with high-order pooling is proposed to…
Brain Stroke Lesion Segmentation Using Consistent Perception Generative Adversarial Network
Shuqiang Wang, Zhuo Chen, Wen Yu +1
The state-of-the-art deep learning methods have demonstrated impressive performance in segmentation tasks. However, the success of these methods depends on a large amount of manual…
Energy Efficient Resource Allocation for Time-Varying OFDMA Relay Systems with Hybrid Energy Supplies
Bo Yang, Yanyan Shen, Qiaoni Han +3
This paper investigates the energy efficient resource allocation for orthogonal frequency division multiple access (OFDMA) relay systems, where the system is supplied by the conven…