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Classification Methods for Remotely Sensed Data; Third Edition by Taskin Kavzoglu, Brandt Tso, Paul M. Mather, Paul Mather is a nonfiction available to read on EtoBox.

What is Classification Methods for Remotely Sensed Data; Third Edition about?

The third edition of the bestselling Classification Methods for Remotely Sensed Data covers current state-of-the-art machine learning algorithms and developments in the analysis of remotely sensed data. This book is thoroughly updated to meet the needs of readers today and provides six new chapters on deep learning, feature extraction and selection, multisource image fusion, hyperparameter optimization, accuracy assessment with model explainability, and object-based image analysis, which is relatively a new paradigm in image processing and classification. It presents new AI-based analysis tools and metrics together with ongoing debates on accuracy assessment strategies and XAI methods. New in this edition: Provides comprehensive background on the theory of deep learning and its application to remote sensing data. Includes a chapter on hyperparameter optimization techniques to guarantee the highest performance in classification applications. Outlines the latest strategies and accuracy measures in accuracy assessment and summarizes accuracy metrics and assessment strategies. Discusses the methods used for explaining inherent structures and weighing the features of

Who reads Classification Methods for Remotely Sensed Data; Third Edition?

Author

Taskin Kavzoglu, Brandt Tso, Paul M. Mather, Paul Mather

Publisher

CRC Press LLC

Published

2024

Language

EN

ISBN

9781040099056

Category

nonfiction

Subjects

Engineering, Science, Anthropology