24 citations · 67 across the 10 of their papers we have counts for
10 papers
MHNet: Multi-view High-order Network for Diagnosing Neurodevelopmental Disorders Using Resting-state fMRI
Yueyang Li, Weiming Zeng, Wenhao Dong +6
Background: Deep learning models have shown promise in diagnosing neurodevelopmental disorders (NDD) like ASD and ADHD. However, many models either use graph neural networks (GNN)…
You Only Acquire Sparse-channel (YOAS): A Unified Framework for Dense-channel EEG Generation
Hongyu Chen, Weiming Zeng, Luhui Cai +6
High-precision acquisition of dense-channel electroencephalogram (EEG) signals is often impeded by the costliness and lack of portability of equipment. In contrast, generating dens…
MM-GTUNets: Unified Multi-Modal Graph Deep Learning for Brain Disorders Prediction
Luhui Cai, Weiming Zeng, Hongyu Chen +7
Graph deep learning (GDL) has demonstrated impressive performance in predicting population-based brain disorders (BDs) through the integration of both imaging and non-imaging data.…
Multi-View Vertebra Localization and Identification from CT Images
Han Wu, Jiadong Zhang, Yu Fang +4
Accurately localizing and identifying vertebrae from CT images is crucial for various clinical applications. However, most existing efforts are performed on 3D with cropping patch…
Hierarchical Bayesian inference for community detection and connectivity of functional brain networks
Lingbin Bian, Nizhuan Wang, Leonardo Novelli +2
Most functional magnetic resonance imaging studies rely on estimates of hierarchically organized functional brain networks whose segregation and integration reflect the cognitive a…
A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion
Xiangxi Meng, Yuning Gu, Yongsheng Pan +6
Multi-modal medical image completion has been extensively applied to alleviate the missing modality issue in a wealth of multi-modal diagnostic tasks. However, for most existing sy…
WSEBP: A Novel Width-depth Synchronous Extension-based Basis Pursuit Algorithm for Multi-Layer Convolutional Sparse Coding
Haitong Tang, Shuang He, Lingbin Bian +2
The pursuit algorithms integrated in multi-layer convolutional sparse coding (ML-CSC) can interpret the convolutional neural networks (CNNs). However, many current state-of-art (SO…
MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification
Shuang He, Haitong Tang, Xia Lu +2
It is well known that hyperspectral images (HSI) contain rich spatial-spectral contextual information, and how to effectively combine both spectral and spatial information using DN…
RSI-Net: Two-Stream Deep Neural Network for Remote Sensing Imagesbased Semantic Segmentation
Shuang He, Xia Lu, Jason Gu +6
For semantic segmentation of remote sensing images (RSI), trade-off between representation power and location accuracy is quite important. How to get the trade-off effectively is a…
CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentation
Haitong Tang, Shuang He, Mengduo Yang +5
It is a challenging task to accurately perform semantic segmentation due to the complexity of real picture scenes. Many semantic segmentation methods based on traditional deep lear…