Deep Learning Algorithms
eBook - PDF

Deep Learning Algorithms

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  1. 408 pages
  2. English
  3. PDF
  4. Available on iOS & Android
eBook - PDF

Deep Learning Algorithms

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About this book

This book covers different topics from deep learning algorithms, including: methods and approaches for deep learning, deep learning applications in biology, deep learning applications in medicine, and deep learning applications in pattern recognition systems.Section 1 focuses on methods and approaches for deep learning, describing advancements in deep learning theory and applications - perspective in 2020 and beyond; deep ensemble reinforcement learning with multiple deep deterministic policy gradient algorithm; dynamic decision-making for stabilized deep learning software platforms; deep learning for hyperspectral data classification through exponential momentum deep convolution neural networks; and ensemble network architecture for deep reinforcement learning.Section 2 focuses on deep learning applications in biology, describing fish detection using deep learning; deep learning identification of tomato leaf disease; deep learning for plant identification in natural environment; and applying deep learning models to mouse behavior recognition.Section 3 focuses on deep learning applications in medicine, describing application of deep learning in neuroradiology: brain hemorrhage classification using transfer learning; a review of the application of deep learning in brachytherapy; exploring deep learning and transfer learning for colonic polyp classification; and deep learning algorithm for brain-computer interface.Section 4 focuses on deep learning applications in pattern recognition systems, describing application of deep learning in airport visibility forecast; hierarchical representations feature deep learning for face recognition; review of research on text sentiment analysis based on deep learning; classifying hand written digits with deep learning; and bitcoin price prediction based on deep learning methods.

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Information

Table of contents

  1. Cover
  2. Title Page
  3. Copyright
  4. DECLARATION
  5. ABOUT THE EDITOR
  6. TABLE OF CONTENTS
  7. List of Contributors
  8. List of Abbreviations
  9. Preface
  10. Section 1: Methods and Approaches for Deep Learning
  11. Section 2: Deep Learning Techniques Applied in Biology
  12. Section 3: Deep learning Applications in Medicine
  13. Section 4: Deep Learning in Pattern Recognition Tasks
  14. Index
  15. Back Cover