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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Vydáno v:	IEEE transaction on neural networks and learning systems Ročník 35; číslo 1; s. 1157 - 1171
Hlavní autoři:	Jia, Sen, Jiang, Shuguo, Zhang, Shuyu, Xu, Meng, Jia, Xiuping
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States IEEE 01.01.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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
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