Dual Graph U-Nets for Hyperspectral Image Classification

Dual Graph U-Nets for Hyperspectral Image Classification

Graph convolutional neural networks (GCNs) have been widely used in hyperspectral images (HSIs) classification for their superiority in processing non-Euclidean structure data. The performance of GCNs relies on the initial graph structure. Most GCN models only utilize spectral information to constru...

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Bibliographic Details
Main Authors:	Fangming Guo, Zhongwei Li, Ziqi Xin, Xue Zhu, Leiquan Wang, Jie Zhang
Format:	Article
Language:	English
Published:	IEEE 2021-01-01
Series:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:	Graph convolutional networks(GCN) hyperspectral image (HSI) classification spectral-spatial fusion spectral-spatial graph
Online Access:	https://ieeexplore.ieee.org/document/9511023/

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