
Deep Learning in Visual Computing and Signal Processing
- 270 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
Deep Learning in Visual Computing and Signal Processing
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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Information
Table of contents
- Cover Page
- Half Title page
- Title Page
- Copyright Page
- Contents
- Contributors
- Abbreviations
- Preface
- 1. Deep Learning Architecture and Framework
- 2. Deep Learning in Neural Networks: An Overview
- 3. Deep Learning: Current Trends and Techniques
- 4. TensorFlow: Machine Learning Using Heterogeneous Edge on Distributed Systems
- 5. Introduction to Biorobotics: Part of Biomedical Signal Processing
- 6. Deep Learning-Based Object Recognition and Detection Model
- 7. Deep Learning: A Pathway for Automated Brain Tumor Segmentation in MRI Images
- 8. Recurrent Neural Networks and Their Application in Seizure Classification
- 9. Brain Tumor Classification Using Convolutional Neural Network
- 10. A Proactive Improvement Toward Digital Forensic Investigation Based on Deep Learning
- Index