Spatial-Pooling-Based Graph Attention U-Net for Hyperspectral Image Classification

Spatial-Pooling-Based Graph Attention U-Net for Hyperspectral Image Classification

In recent years, graph convolutional networks (GCNs) have attracted increasing attention in hyperspectral image (HSI) classification owing to their exceptional representation capabilities. However, the high computational requirements of GCNs have led most existing GCN-based HSI classification method...

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Bibliographic Details
Main Authors:	Qi Diao, Yaping Dai, Jiacheng Wang, Xiaoxue Feng, Feng Pan, Ce Zhang
Format:	Article
Language:	English
Published:	MDPI AG 2024-03-01
Series:	Remote Sensing
Subjects:	graph convolutional network dynamic graph attention mechanism hyperspectral image classification
Online Access:	https://www.mdpi.com/2072-4292/16/6/937

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