Suchergebnisse - "Graph convolutional network"

Graph‐convolutional‐network‐based interactive prostate segmentation in MR images von Tian, Zhiqiang, Li, Xiaojian, Zheng, Yaoyue, Chen, Zhang, Shi, Zhong, Liu, Lizhi, Fei, Baowei

“… Methods We propose an interactive segmentation method based on a graph convolutional network (GCN …”
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PGCN: Pyramidal Graph Convolutional Network for EEG Emotion Recognition von Jin, Ming, Du, Changde, He, Huiguang, Cai, Ting, Li, Jinpeng

“… In the last decade, electroencephalogram (EEG)-based emotion recognition has been intensively investigated due to its prominative accuracy and reliability, and graph convolutional network (GCN …”
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A Mutual Multi-Scale Triplet Graph Convolutional Network for Classification of Brain Disorders Using Functional or Structural Connectivity von Yao, Dongren, Sui, Jing, Wang, Mingliang, Yang, Erkun, Jiaerken, Yeerfan, Luo, Na, Yap, Pew-Thian, Liu, Mingxia, Shen, Dinggang

“… Capturing network topology, graph convolutional networks (GCNs) have demonstrated to be superior in learning network representations tailored for identifying specific brain disorders …”
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Multi-relation graph convolutional network for Alzheimer’s disease diagnosis using structural MRI von Zhang, Jin, He, Xiaohai, Qing, Linbo, Chen, Xiang, Liu, Yan, Chen, Honggang

“… Structural magnetic resonance imaging (sMRI) is widely applied in Alzheimer’s disease (AD) diagnosis tasks by reflecting structural anomalies of the brain …”
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Skeleton-based human action evaluation using graph convolutional network for monitoring Alzheimer’s progression von Yu, Bruce X.B., Liu, Yan, Chan, Keith C.C., Yang, Qintai, Wang, Xiaoying

“… •We propose a novel two-task graph convolutional network (2T-GCN) to represent skeleton data for human action evaluation (HAE …”
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Multi-scale enhanced graph convolutional network for mild cognitive impairment detection von Lei, Baiying, Zhu, Yun, Yu, Shuangzhi, Hu, Huoyou, Xu, Yanwu, Yue, Guanghui, Wang, Tianfu, Zhao, Cheng, Chen, Shaobin, Yang, Peng, Song, Xuegang, Xiao, Xiaohua, Wang, Shuqiang

“… •We design a MCI-graph framework which integrates both non-image information and image information. We use LWCC to extract the feature to avoid the high …”
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Early detection of Parkinson’s disease using a multi area graph convolutional network von Huo, Hua, Zhang, Chen, Liu, Wei, Zhao, Changwei, Ma, Lan, Wang, Jinxuan, Xu, Ningya

“… introduces an innovative deep learning approach, namely Multi-area Attention Spatiotemporal Directed Graph Convolutional Network (Ma-ST-DGN …”
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An extensible hierarchical graph convolutional network for early Alzheimer’s disease identification von Tian, Xu, Liu, Yan, Wang, Ling, Zeng, Xiangzhu, Huang, Yulang, Wang, Zeng

“… : In this study, we propose an extensible hierarchical graph convolutional network (EH-GCN) for early AD identification …”
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ADMGCN: Graph Convolutional Network for Alzheimer’s Disease Diagnosis with a Meta-learning Paradigm von Sun, Xiaowen, Li, Jiahao, Yan, Guiying, Han, Renmin

“… While graph convolutional networks (GCNs) have emerged as popular tools for AD diagnosis due to their ability to handle structural information and fuse multi-modal features, deep learning approaches face significant challenges including …”
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Alzheimer's disease classification using mutual information generated graph convolutional network for functional MRI von Fu, Yinghua, Jiang, Li, Detre, John, Wang, Ze

“… ) through a connectome-based graph convolutional network (GCN).MethodsMI was calculated between the mean time series of each pair of brain regions, forming the connectome which was input to a multi-level connectome based GCN (MLC-GCN …”
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Ensemble Manifold Regularized Multi-Modal Graph Convolutional Network for Cognitive Ability Prediction von Qu, Gang, Xiao, Li, Hu, Wenxing, Wang, Junqi, Zhang, Kun, Calhoun, Vince, Wang, Yu-Ping

“… : To take advantage of complementary information from multi-modal fMRI, we propose an interpretable multi-modal graph convolutional network (MGCN …”
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Hierarchical Graph Convolutional Network Built by Multiscale Atlases for Brain Disorder Diagnosis Using Functional Connectivity von Liu, Mianxin, Zhang, Han, Shi, Feng, Shen, Dinggang

“… )." Accordingly, we propose a multiscale-atlases-based hierarchical graph convolutional network (MAHGCN …”
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Multipattern graph convolutional network-based autism spectrum disorder identification von Zhou, Wenhao, Sun, Mingxiang, Xu, Xiaowen, Ruan, Yudi, Sun, Chenhao, Li, Weikai, Gao, Xin

“… As a promising strategy, graph convolutional networks (GCN) provide an attractive approach to simultaneously extract FBN features and facilitate ASD identification, thus replacing the manual feature extraction from FBN …”
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Augmented Multicenter Graph Convolutional Network for COVID-19 Diagnosis von Song, Xuegang, Li, Haimei, Gao, Wenwen, Chen, Yue, Wang, Tianfu, Ma, Guolin, Lei, Baiying

“… To address this issue, we propose an augmented multicenter graph convolutional network (AM-GCN) to diagnose COVID-19 with steps as follows …”
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A Deep Learning Approach for Long-Term Traffic Flow Prediction With Multifactor Fusion Using Spatiotemporal Graph Convolutional Network von Qi, Xiaoyu, Mei, Gang, Tu, Jingzhi, Xi, Ning, Piccialli, Francesco

“… on a spatiotemporal graph convolutional network for long-term traffic flow prediction with multiple factors …”
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A novel unsupervised domain adaptation framework based on graph convolutional network and multi-level feature alignment for inter-subject ECG classification von He, Ziyang, Chen, Yufei, Yuan, Shuaiying, Zhao, Jianhui, Yuan, Zhiyong, Polat, Kemal, Alhudhaif, Adi, Alenezi, Fayadh, Hamid, Arwa

“… ) module to extract spatio-temporal features of the samples. Then the graph convolutional network (GCN …”
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Multi-scale temporal features extraction based graph convolutional network with attention for multivariate time series prediction von Chen, Yawen, Ding, Fengqian, Zhai, Linbo

“… Modeling for multivariate time series have always been a meaningful subject. Multivariate time series forecasting is a fundamental problem attracting many researchers in various fields …”
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Information cascade prediction of complex networks based on physics-informed graph convolutional network von Yu, Dingguo, Zhou, Yijie, Zhang, Suiyu, Li, Wenbing, Small, Michael, Shang, Ke-ke

“… In this paper, we propose a novel framework called Physics-informed graph convolutional network (PiGCN …”
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Feature reconstruction graph convolutional network for skeleton-based action recognition von Huang, Junhao, Wang, Ziming, Peng, Jian, Huang, Feihu

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A Graph Convolutional Network Based on Univariate Neurodegeneration Biomarker for Alzheimer's Disease Diagnosis von Qu, Zongshuai, Yao, Tao, Liu, Xinghui, Wang, Gang

“… This study proposed an efficient method of applying a graph convolutional network (GCN) on the early prediction of AD. Methods …”
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