Classification Methods for Remotely Sensed Data
eBook - ePub

Classification Methods for Remotely Sensed Data

  1. 444 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Classification Methods for Remotely Sensed Data

About this book

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 ML and AI algorithms that are critical for explaining the robustness of the models.

This book is intended for industry professionals, researchers, academics, and graduate students who want a thorough and up-to-date guide to the many and varied techniques of image classification applied in the fields of geography, geospatial and earth sciences, electronic and computer science, environmental engineering, etc.

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Yes, you can access Classification Methods for Remotely Sensed Data by Taskin Kavzoglu,Brandt Tso,Paul M. Mather in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Geology & Earth Sciences. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Table of Contents
  7. Preface to the Third Edition
  8. Preface to the Second Edition
  9. Preface to the First Edition
  10. Acknowledgments
  11. Authors
  12. Chapter 1 Fundamentals of Remote Sensing
  13. Chapter 2 Pattern Recognition Principles
  14. Chapter 3 Dimensionality Reduction: Feature Extraction and Selection
  15. Chapter 4 Multisource Image Fusion and Classification
  16. Chapter 5 Support Vector Machines
  17. Chapter 6 Decision Trees
  18. Chapter 7 Deep Learning
  19. Chapter 8 Object-Based Image Analysis
  20. Chapter 9 Hyperparameter Optimization
  21. Chapter 10 Accuracy Assessment and Model Explainability
  22. Index