Results 21 to 30 of about 13,926 (236)
IET Image Processing, 2022 Skeleton‐based action recognition is an inspired yet challenging task in computer vision. Recently, the latest graph convolutional network (GCN), which generalises well‐established convolutional neural networks to non‐Euclidean structures, is proven to ...
Jun Tang +4 more
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GCN Global Communications Newsletter [PDF]
IEEE Communications Magazine, 2020 With this issue we begin a new series of eight interviews with the Officers of the IEEE ComSoc Member and Global Activities (MGA) Council, which will be published every month in the Global Communications Newsletter.
Stefano Bregni +3 more
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Heliyon, 2023 The extensive consumption of fossil fuels increases CO2 concentration in the atmosphere, resulting in serious global warming problems. Meanwhile, the problem of water contamination by organic substances is another significant global challenge.
Chiing-Chang Chen +7 more
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Quadratic GCN for Graph Classification
CoRR, 2021 Graph Convolutional Networks (GCNs) have been extensively used to classify vertices in graphs and have been shown to outperform other vertex classification methods. GCNs have been extended to graph classification tasks (GCT). In GCT, graphs with different numbers of edges and vertices belong to different classes, and one attempts to predict the graph ...
Omer Nagar +3 more
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, 2023 Towards Sufficient Power-Traffic Coordination: GCN-based Prediction of Spatial-Temporal EV Charging ...
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Analyzing GCN Aggregation on GPU
IEEE Access, 2022 Graph convolutional neural networks (GCNs) are emerging neural networks for graph structures that include large features associated with each vertex. The operations of GCN can be divided into two phases - aggregation and combination. While the combination just performs matrix multiplications using trained weights and aggregated features, the ...
Inje Kim +4 more
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Frontiers in Sensors, 2022 In this study a nanocomposite of graphitic carbon nitride-silver polyvinylpyrrolidone (gCN-AgPVP) was fabricated for the electrochemical detection of paracetamol (PAR).
N. Mekgoe, N. Mabuba, K. Pillay
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Spammer detection technology of social network based on graph convolution network
网络与信息安全学报, 2018 In social networks,Spammer send advertisements that are useless to recipients without the recipient's permission,seriously threatening the information security of normal users and the credit system of social networking sites.In order to solve problems of
Qiang QU,Hongtao YU,Ruiyang HUANG
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Development of photocatalysis‐membrane separation reactor systems for aqueous pollutant removal
PhotoMat, EarlyView., 2023 Abstract Background In our rapidly expanding society, the demand for clean water has steadily emerged as one of the most critical issues, promoting the development of numerous water treatment strategies. Aims Coupling photocatalysis and membrane separation technology provides an energy saving and environment‐friendly as well as sustainable method for ...
Junyang Zhang +3 more
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IEEE Access, 2022 Graph Convolutional Network (GCN) has achieved significant success in many graph representation learning tasks. GCN usually learns graph representations by performing Neighbor Aggregation (NA) and Feature Transformation (FT) operations.
Dezhi Sun, Man Hu, Zhenyu Li
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