Deep Learning in Visual Computing and Signal Processing
  1. 270 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

About this book

An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this new volume covers the fundamentals and advanced topics in designing and deploying techniques using deep architectures and their application in visual computing and signal processing.

The volume first lays out the fundamentals of deep learning as well as deep learning architectures and frameworks. It goes on to discuss deep learning in neural networks and deep learning for object recognition and detection models. It looks at the various specific applications of deep learning in visual and signal processing, such as in biorobotics, for automated brain tumor segmentation in MRI images, in neural networks for use in seizure classification, for digital forensic investigation based on deep learning, and more.

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Yes, you can access Deep Learning in Visual Computing and Signal Processing by Krishna Kant Singh, Vibhav Kumar Sachan, Akansha Singh, Sanjeevikumar Padmanaban, Krishna Kant Singh,Vibhav Kumar Sachan,Akansha Singh,Sanjeevikumar Padmanaban in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Science General. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover Page
  2. Half Title page
  3. Title Page
  4. Copyright Page
  5. Contents
  6. Contributors
  7. Abbreviations
  8. Preface
  9. 1. Deep Learning Architecture and Framework
  10. 2. Deep Learning in Neural Networks: An Overview
  11. 3. Deep Learning: Current Trends and Techniques
  12. 4. TensorFlow: Machine Learning Using Heterogeneous Edge on Distributed Systems
  13. 5. Introduction to Biorobotics: Part of Biomedical Signal Processing
  14. 6. Deep Learning-Based Object Recognition and Detection Model
  15. 7. Deep Learning: A Pathway for Automated Brain Tumor Segmentation in MRI Images
  16. 8. Recurrent Neural Networks and Their Application in Seizure Classification
  17. 9. Brain Tumor Classification Using Convolutional Neural Network
  18. 10. A Proactive Improvement Toward Digital Forensic Investigation Based on Deep Learning
  19. Index