25 citations · 46 across the 3 of their papers we have counts for
4 papers
GCN-SL: Graph Convolutional Networks with Structure Learning for Graphs under Heterophily
Mengying Jiang, Guizhong Liu, Yuanchao Su +1
In representation learning on the graph-structured data, under heterophily (or low homophily), many popular GNNs may fail to capture long-range dependencies, which leads to their p…
R-GSN: The Relation-based Graph Similar Network for Heterogeneous Graph
Xinliang Wu, Mengying Jiang, Guizhong Liu
Heterogeneous graph is a kind of data structure widely existing in real life. Nowadays, the research of graph neural network on heterogeneous graph has become more and more popular…
Linear vs Nonlinear Extreme Learning Machine for Spectral-Spatial Classification of Hyperspectral Image
Faxian Cao, Zhijing Yang, Jinchang Ren +2
As a new machine learning approach, extreme learning machine (ELM) has received wide attentions due to its good performances. However, when directly applied to the hyperspectral im…
Does Normalization Methods Play a Role for Hyperspectral Image Classification?
Faxian Cao, Zhijing Yang, Jinchang Ren +2
For Hyperspectral image (HSI) datasets, each class have their salient feature and classifiers classify HSI datasets according to the class's saliency features, however, there will…