Results 11 to 20 of about 1,216 (173)
HyperGraph-based capsule temporal memory network for efficient and explainable diabetic retinopathy detection in retinal imaging [PDF]
Scientific ReportsDiabetic retinopathy (DR) is a chronic complication of diabetes in which the retinal damage may cause vision impairment or blindness if left untreated. The challenges in DR detection are mostly due to the morphological variations of retinal lesions, e.g.,
Mishmala Sushith +3 more
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Directed hypergraph neural network [PDF]
CoRR, 2020 To deal with irregular data structure, graph convolution neural networks have been developed by a lot of data scientists. However, data scientists just have concentrated primarily on developing deep neural network method for un-directed graph. In this paper, we will present the novel neural network method for directed hypergraph. In the other words, we
Loc Hoang Tran, Linh Hoang Tran
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A Dual Neighborhood Hypergraph Neural Network for Change Detection in VHR Remote Sensing Images
Remote Sensing, 2023 The very high spatial resolution (VHR) remote sensing images have been an extremely valuable source for monitoring changes occurring on the Earth’s surface. However, precisely detecting relevant changes in VHR images still remains a challenge, due to the
Junzheng Wu +6 more
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Model of the malicious traffic classification based on hypergraph neural network
网络与信息安全学报, 2023 As the use and reliance on networks continue to grow, the prevalence of malicious network traffic poses a significant challenge in the field of network security.Cyber attackers constantly seek new ways to infiltrate systems, steal data, and disrupt ...
Wenbo ZHAO, Zitong MA, Zhe YANG
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Multi-site Hyper-graph Convolutional Neural Networks and Application [PDF]
Jisuanji kexue, 2022 Recently,the exploitation of graph neural networks for neurological brain disorder diagnosis has attracted much attention.However,the graphs used in the existing studies are usually based on the pairwise connections of different nodes,and thus cannot ...
ZHOU Hai-yu, ZHANG Dao-qiang
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Directed hypergraph attention network for traffic forecasting
IET Intelligent Transport Systems, 2022 In traffic systems, traffic forecasting is a critical issue, which has attracted much interest from researchers. It is a challenging task due to the complex spatial‐temporal patterns of traffic data.
Xiaoyi Luo, Jiaheng Peng, Jun Liang
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Signal Contrastive Enhanced Graph Collaborative Filtering for Recommendation
Data Science and Engineering, 2023 Graph collaborative filtering methods have shown great performance improvements compared with deep neural network-based models. However, these methods suffer from data sparsity and data noise problems.
Zhi-Yuan Li +3 more
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Dynamic Hypergraph Neural Networks [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 In recent years, graph/hypergraph-based deep learning methods have attracted much attention from researchers. These deep learning methods take graph/hypergraph structure as prior knowledge in the model. However, hidden and important relations are not directly represented in the inherent structure.
Jianwen Jiang +4 more
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Equivariant Hypergraph Neural Networks
, 2022 Many problems in computer vision and machine learning can be cast as learning on hypergraphs that represent higher-order relations. Recent approaches for hypergraph learning extend graph neural networks based on message passing, which is simple yet fundamentally limited in modeling long-range dependencies and expressive power. On the other hand, tensor-
Jinwoo Kim +3 more
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IEEE Access, 2023 With the increasingly competitive job market, the employment issue for college graduates has received more and more attention. Predicting graduation development can help students understand their suitable graduation development, thus easing the pressure ...
Yong Ouyang +4 more
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