Search Results for author: Nizhuan Wang

Found 9 papers, 5 papers with code

MM-GTUNets: Unified Multi-Modal Graph Deep Learning for Brain Disorders Prediction

no code implementations20 Jun 2024 Luhui Cai, Weiming Zeng, Hongyu Chen, Hua Zhang, Yueyang Li, Hongjie Yan, Lingbin Bian, Nizhuan Wang

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.

Graph Learning Representation Learning

Multi-View Vertebra Localization and Identification from CT Images

1 code implementation24 Jul 2023 Han Wu, Jiadong Zhang, Yu Fang, Zhentao Liu, Nizhuan Wang, Zhiming Cui, Dinggang Shen

Additionally, we further propose a Sequence Loss to maintain the sequential structure embedded along the vertebrae.

Contrastive Learning

Underwater target detection based on improved YOLOv7

1 code implementation14 Feb 2023 Kaiyue Liu, Qi Sun, Daming Sun, Mengduo Yang, Nizhuan Wang

Underwater target detection is a crucial aspect of ocean exploration.

Hierarchical Bayesian inference for community detection and connectivity of functional brain networks

1 code implementation18 Jan 2023 Lingbin Bian, Nizhuan Wang, Leonardo Novelli, Jonathan Keith, Adeel Razi

The method can robustly detect the group-level community structure of weighted functional networks that give rise to hidden brain states with an unknown number of communities and retain the variability of individual networks.

Bayesian Inference Community Detection

A Novel Unified Conditional Score-based Generative Framework for Multi-modal Medical Image Completion

no code implementations7 Jul 2022 Xiangxi Meng, Yuning Gu, Yongsheng Pan, Nizhuan Wang, Peng Xue, Mengkang Lu, Xuming He, Yiqiang Zhan, Dinggang Shen

Multi-modal medical image completion has been extensively applied to alleviate the missing modality issue in a wealth of multi-modal diagnostic tasks.

WSEBP: A Novel Width-depth Synchronous Extension-based Basis Pursuit Algorithm for Multi-Layer Convolutional Sparse Coding

1 code implementation28 Mar 2022 Haitong Tang, Shuang He, Lingbin Bian, Zhiming Cui, Nizhuan Wang

Specifically, we first propose a novel width-depth synchronous extension-based basis pursuit (WSEBP) algorithm which solves the ML-CSC problem without the limitation of the number of iterations compared to the SOTA algorithms and maximizes the performance by an effective initialization in each layer.

Image Classification

MSHCNet: Multi-Stream Hybridized Convolutional Networks with Mixed Statistics in Euclidean/Non-Euclidean Spaces and Its Application to Hyperspectral Image Classification

no code implementations7 Oct 2021 Shuang He, Haitong Tang, Xia Lu, Hongjie Yan, Nizhuan Wang

Specifically, our MSHCNet adopted four parallel streams, which contained G-stream, utilizing the irregular correlation between adjacent land covers in terms of first-order graph in non-Euclidean space; C-stream, adopting convolution operator to learn regular spatial-spectral features in Euclidean space; N-stream, combining first and second order features to learn representative and discriminative regular spatial-spectral features of Euclidean space; S-stream, using GSOP to capture boundary correlations and obtain graph representations from all nodes in graphs of non-Euclidean space.

Hyperspectral Image Classification

CSC-Unet: A Novel Convolutional Sparse Coding Strategy Based Neural Network for Semantic Segmentation

1 code implementation1 Aug 2021 Haitong Tang, Shuang He, Mengduo Yang, Xia Lu, Qin Yu, Kaiyue Liu, Hongjie Yan, Nizhuan Wang

Through extensive analysis and experiments, we provided credible evidence showing that the multi-layer convolutional sparse coding block enables semantic segmentation model to converge faster, can extract finer semantic and appearance information of images, and improve the ability to recover spatial detail information.

Segmentation Semantic Segmentation

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