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Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images
Hoofdkenmerken
Auteur: Yao Ding; Zhili Zhang; Haojie Hu; Fang He; Shuli Cheng; Yijun Zhang
Titel: Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images
Uitgever: Springer Nature
ISBN: 9789819780099
ISBN boekversie: 9789819780082
Prijs: € 167.85
Verschijningsdatum: 26-11-2024
Inhoudelijke kenmerken
Categorie: Intelligence (AI) & Semantics
Taal: English
Imprint: Springer
Technische kenmerken
Verschijningsvorm: E-book
 

Inhoudsopgave:

This book deals with hyperspectral image classification using graph neural network methods, focusing on classification model designing, graph information dissemination, and graph construction. In the book, various graph neural network based classifiers have been proposed for hyperspectral image classification to improve the classification accuracy. This book has promoted the application of graph neural network in hyperspectral image classification, providing reference for remote sensing image processing. It will be a useful reference for researchers in remote sensing image processing and image neural network design.
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