SORAG: Synthetic Data Over-Sampling Strategy on Multi-Label Graphs

SORAG: Synthetic Data Over-Sampling Strategy on Multi-Label Graphs

In many real-world networks of interest in the field of remote sensing (e.g., public transport networks), nodes are associated with multiple labels, and node classes are imbalanced; that is, some classes have significantly fewer samples than others. However, the research problem of imbalanced multi-...

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Bibliographic Details
Main Authors:	Yijun Duan, Xin Liu, Adam Jatowt, Hai-tao Yu, Steven Lynden, Kyoung-Sook Kim, Akiyoshi Matono
Format:	Article
Language:	English
Published:	MDPI AG 2022-09-01
Series:	Remote Sensing
Subjects:	imbalanced data classification data over-sampling generative adversarial network graph convolutional network semi-supervised learning remote sensing
Online Access:	https://www.mdpi.com/2072-4292/14/18/4479

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