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

£119.99

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

Mathematical modelling Electronics engineering Machine learning Image processing

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

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Collection: Intelligent Perception and Information Processing

Language: English

Published by: Springer

Published on: 26th November 2024

Format: LCP-protected ePub

ISBN: 9789819780099


Hyperspectral Image Classification with Graph Neural Networks

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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