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

Language EnglishEnglish
E-book Adobe ePub DRM
Publishers Springer, November 2024
This book deals with hyperspectral image classification using graph neural network methods, focusing... Full description
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167.16 €
326.93  лв
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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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About the book

Full name Graph Neural Network for Feature Extraction and Classification of Hyperspectral Remote Sensing Images
Author Yao Ding, Zhili Zhang, Haojie Hu, Fang He, Shuli Cheng, Yijun Zhang
Language English
Binding E-book - Adobe ePub DRM
Date of issue 2024
EAN 9789819780099
Libristo code 47825395
Publishers Springer

Categories

Mathematics & Science > Mathematics > Applied mathematics > Mathematical modelling
Computing & Information Technology > Computer science > Artificial intelligence > Machine learning
Earth Sciences, Geography, Environment, Planning > Geography > Geographical information systems & remote sensing
Technology, Engineering, Agriculture > Electronics & communications engineering > Electronics engineering
Computing & Information Technology > Computer science > Image processing
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