14.5.7.5.1 Graph Convolutional Neural Networks

Chapter Contents (Back)
Convolutional Neural Networks. Neural Networks. Graph Convolutional Neural Networks.

Fu, S.[Sichao], Liu, W.F.[Wei-Feng], Li, S.Y.[Shu-Ying], Zhou, Y.C.[Yi-Cong],
Two-order graph convolutional networks for semi-supervised classification,
IET-IPR(13), No. 14, 12 December 2019, pp. 2763-2771.
DOI Link 1912
BibRef

Zhang, Z.H.[Zhi-Hong], Chen, D.D.[Dong-Dong], Wang, J.J.[Jian-Jia], Bai, L.[Lu], Hancock, E.R.[Edwin R.],
Quantum-based subgraph convolutional neural networks,
PR(88), 2019, pp. 38-49.
Elsevier DOI 1901
Graph convolutional neural networks, Spatial construction, Quantum walks, Subgraph BibRef

Xu, C.Y.[Chuan-Yu], Wang, D.[Dong], Zhang, Z.H.[Zhi-Hong], Wang, B.[Beizhan], Zhou, D.[Da], Ren, G.J.[Gui-Jun], Bai, L.[Lu], Cui, L.X.[Li-Xin], Hancock, E.R.[Edwin R.],
Depth-based Subgraph Convolutional Neural Networks,
ICPR18(1024-1029)
IEEE DOI 1812
Convolution, Feature extraction, Convolutional neural networks, Standards, Task analysis, Data mining, Laplace equations BibRef

Zhang, Z.H.[Zhi-Hong], Chen, D.D.[Dong-Dong], Wang, Z.[Zeli], Li, H.[Heng], Bai, L.[Lu], Hancock, E.R.[Edwin R.],
Depth-based subgraph convolutional auto-encoder for network representation learning,
PR(90), 2019, pp. 363-376.
Elsevier DOI 1903
Graph based CNN style learning. Network representation learning, Graph convolutional neural network, Node classification BibRef

Chen, Y.X.[Yu-Xin], Ma, G.[Gaoqun], Yuan, C.F.[Chun-Feng], Li, B.[Bing], Zhang, H.[Hui], Wang, F.[Fangshi], Hu, W.M.[Wei-Ming],
Graph convolutional network with structure pooling and joint-wise channel attention for action recognition,
PR(103), 2020, pp. 107321.
Elsevier DOI 2005
Graph convolutional network, Structure graph pooling, Joint-wise channel attention BibRef

Wan, S.[Sheng], Gong, C.[Chen], Zhong, P.[Ping], Du, B.[Bo], Zhang, L.F.[Le-Fei], Yang, J.[Jian],
Multiscale Dynamic Graph Convolutional Network for Hyperspectral Image Classification,
GeoRS(58), No. 5, May 2020, pp. 3162-3177.
IEEE DOI 2005
Hyperspectral imaging, Convolution, Feature extraction, Kernel, Support vector machines, Training, Dynamic graph, multiscale information BibRef

Luo, Y.[Yawei], Ji, R.R.[Rong-Rong], Guan, T.[Tao], Yu, J.Q.[Jun-Qing], Liu, P.[Ping], Yang, Y.[Yi],
Every node counts: Self-ensembling graph convolutional networks for semi-supervised learning,
PR(106), 2020, pp. 107451.
Elsevier DOI 2006
Teacher-student models, Self-ensemble learning, Graph convolutional networks, Semi-supervised learning BibRef


Park, J.[Jiwoong], Lee, M.[Minsik], Chang, H.J.[Hyung Jin], Lee, K.[Kyuewang], Choi, J.Y.[Jin Young],
Symmetric Graph Convolutional Autoencoder for Unsupervised Graph Representation Learning,
ICCV19(6518-6527)
IEEE DOI 2004
data visualisation, decoding, encoding, graph theory, image representation, learning (artificial intelligence), BibRef

Mosella-Montoro, A., Ruiz-Hidalgo, J.,
Residual Attention Graph Convolutional Network for Geometric 3D Scene Classification,
GMDL19(4123-4132)
IEEE DOI 2004
computational geometry, convolutional neural nets, feature extraction, image classification, image colour analysis, agc BibRef

Sun, H.L.[Hao-Liang], Zhen, X.T.[Xian-Tong], Yin, Y.L.[Yi-Long],
Learning the Set Graphs: Image-Set Classification Using Sparse Graph Convolutional Networks,
ICIP19(4554-4558)
IEEE DOI 1910
Set graph learning, Graph convolutional network, l1,2-Norm, Image-set classification BibRef

Chen, Z.M.[Zhao-Min], Wei, X.S.[Xiu-Shen], Wang, P.[Peng], Guo, Y.[Yanwen],
Multi-Label Image Recognition With Graph Convolutional Networks,
CVPR19(5172-5181).
IEEE DOI 2002
BibRef

Pope, P.E.[Phillip E.], Kolouri, S.[Soheil], Rostami, M.[Mohammad], Martin, C.E.[Charles E.], Hoffmann, H.[Heiko],
Explainability Methods for Graph Convolutional Neural Networks,
CVPR19(10764-10773).
IEEE DOI 2002
BibRef

Zhang, L.[Ling], Zhu, Z.[Zhigang],
Unsupervised Feature Learning for Point Cloud Understanding by Contrasting and Clustering Using Graph Convolutional Neural Networks,
3DV19(395-404)
IEEE DOI 1911
Task analysis, Feature extraction, Training, Unsupervised learning, Semantics, Graph convolutional neural network BibRef

Litany, O., Bronstein, A., Bronstein, M., Makadia, A.,
Deformable Shape Completion with Graph Convolutional Autoencoders,
CVPR18(1886-1895)
IEEE DOI 1812
Shape, Task analysis, Training, Strain, Neural networks BibRef

Verma, N.[Nitika], Boyer, E.[Edmond], Verbeek, J.[Jakob],
FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis,
CVPR18(2598-2606)
IEEE DOI 1812
Shape, Convolution, Standards, Visualization, Neural networks BibRef

Edwards, M.[Michael], Xie, X.H.[Xiang-Hua],
Graph Convolutional Neural Network,
BMVC16(xx-yy).
HTML Version. 1805
BibRef

Chapter on Pattern Recognition, Clustering, Statistics, Grammars, Learning, Neural Nets, Genetic Algorithms continues in
Convolutional Neural Networks, Design, Implementation Issues .


Last update:Jul 10, 2020 at 16:03:35