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.
Author(s): Krishna Kant Singh, Vibhav Kumar Sachan, Akansha Singh, Sanjeevikumar Padmanaban
Publisher: CRC Press/Apple Academic Press
Year: 2022
Language: English
Pages: 288
City: Palm Bay
Cover
Half Title
Title Page
Copyright Page
About the Editors
Table of 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
