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An authoritative deep dive into the most recent machine learning approaches to hyperspectral remote sensing image processing
In Machine Learning-Based Hyperspectral Image Processing, distinguished researcher Dr. Bing Zhang delivers an up-to-date discussion of machine learning-based approaches to hyperspectral image analysis. The author comprehensively reviews machine learning approaches to hyperspectral image denoising and super-resolution tasks, offering coverage of a variety of perspectives.
Dr. Zhang also explores the most recent research on machine learning hyperspectral unmixing methods and hyperspectral image classification. He explains the algorithms used for hyperspectral image target and change detection, as well.
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Perfect for postgraduate students and research scientists with an interest in the subject, Machine Learning-Based Hyperspectral Image Processing will also benefit researchers, academicians, and students engaged in machine learning-based approaches to image analysis.
Author: Bing Zhang
ISBN-10: 1394267851
ISBN-13: 9781394267859
Publisher: Wiley-IEEE Press
Language: English
Published: 11/10/2025
Pages: 768
Format: Hardcover
Bing Zhang, PhD, is Full Professor and Deputy Director of the Aerospace Information Research Institute, CAS. He has authored over 300 publications and currently serves as the Chief Editor for the Chinese Journal of Remote Sensing and Associate Editor for the IEEE Transactions on Geoscience and Remote Sensing.
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