Graph-in-Graph Convolutional Network for Hyperspectral Image Classification

With the development of hyperspectral sensors, accessible hyperspectral images (HSIs) are increasing, and pixel-oriented classification has attracted much attention. Recently, graph convolutional networks (GCNs) have been proposed to process graph-structured data in non-Euclidean domains and have be...

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Bibliographic Details

Published in:	IEEE transaction on neural networks and learning systems Vol. 35; no. 1; pp. 1157 - 1171
Main Authors:	Jia, Sen, Jiang, Shuguo, Zhang, Shuyu, Xu, Meng, Jia, Xiuping
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Artificial neural networks Classification Classification algorithms Convolutional codes Convolutional neural networks Deep learning Feature extraction Graph convolutional network (GCN) Graph theory graph-in-graph (GiG) hyperspectral image (HSI) classification Hyperspectral imaging Image classification Machine learning Structured data
ISSN:	2162-237X, 2162-2388, 2162-2388
Online Access:	Get full text
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