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2024 | OriginalPaper | Chapter

2. Graph Sample and Aggregate-Attention Network for Hyperspectral Image Classification

Authors : Yao Ding, Zhili Zhang, Haojie Hu, Fang He, Shuli Cheng, Yijun Zhang

Published in: Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images

Publisher: Springer Nature Singapore

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Abstract

Hyperspectral images (HSIs) provide detailed spectral information through hundreds of (narrow) spectral channels, which can be used to accurately classify diverse materials of interest (Rasti et al. in IEEE Geosci Remote Sens 8(4):60–88, 2020; Zhong et al. in IEEE Trans Neural Netw Learn Syst 12:1–13, 2019). However, the increased dimensionality of such data provides a challenge to conventional techniques, and hyperspectral classification has great research value.

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Metadata
Title
Graph Sample and Aggregate-Attention Network for Hyperspectral Image Classification
Authors
Yao Ding
Zhili Zhang
Haojie Hu
Fang He
Shuli Cheng
Yijun Zhang
Copyright Year
2024
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-97-8009-9_2

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