Computer Science & Information Management

Deep Learning in Visual Computing and Signal Processing Editors: Krishna Kant Singh, PhD Vibhav Kumar Sachan, PhD Akansha Singh, PhD Sanjeevikumar Padmanaban, PhD Ordering Info/Buy Book

Published. Available now. Pub Date: October 2022 Hardback Price: see ordering info Hard ISBN: 9781774638705 E-Book ISBN: 9781003277224 Pages: 288pp w/index Binding Type: Hardback / ebook Notes: 78 b/w illustrations

This new volume, Deep Learning in Visual Computing and Signal Processing, 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.

Key features:

• Covers both the fundamentals and the latest concepts in deep learning
• Presents some of the diverse applications of deep learning in visual computing and signal processing
• Includes over 90 figures and tables to elucidate the text

An enlightening amalgamation of deep learning concepts with visual computing and signal processing applications, this valuable resource will serve as a guide for researchers, engineers, and students who want to have a quick start on learning and/or building deep learning systems. It provides a good theoretical and practical understanding and complete information and knowledge required to understand and build deep learning models from scratch.

CONTENTS:

Preface

1. Deep Learning Architecture and Framework
Ashish Tripathi, Shraddha Upadhaya, Arun Kumar Singh, Krishna Kant Singh, Arush Jain, Pushpa Choudhary, and Prem Chand Vashist

2. Deep Learning in Neural Networks: An Overview
Vidit Shukla and Shilpa Choudhary

3. Deep Learning: Current Trends and Techniques
Bharti Sharma, Arun Balodi, Utku Kose, and Akansha Singh

4. Tensorflow: Machine Learning Using Heterogeneous Edge on Distributed Systems
Dr. R. Ganesh Babu, Dr. A. Nedumaran, Mr. G. Manikandan, and Mrs. R. Selvameena

5. Introduction to Biorobotics: Part of Biomedical Signal Processing
Kashish Srivastava and Shilpa Choudhary

6. Deep Learning Based Object Recognition and Detection Model
Aman Jatain, Khushboo Tripathi, and Shalini Bhaskar Bajaj

7. Deep Learning: A Pathway for Automated Brain Tumor Segmentation in MRI Images
Roohi Sille, Piyush Chauhan, and Durgansh Sharma

8. Recurrent Neural Networks and Their Application in Seizure Classification
Kusumika Krori Dutta, Poornima Sridharan, and Sunny Arokia Swamy Bellary

9. Brain Tumor Classification Using Convolutional Neural Network
M. Jayashree, S. Poornima, V. Megala, and R. K. Pongiannan

10. A Proactive Improvement toward Digital Forensic Investigation Based on Deep Learning
Vidushi, Akash Rajak, Ajay Kumar Shrivastava, and Arun Kumar Tripathi

Index

About the Authors / Editors:
Editors: Krishna Kant Singh, PhD
Faculty of Engineering & Technology, Jain (Deemed-to-be University), Bengaluru, India

Krishna Kant Singh, PhD, is working as Professor and Head, Department of CSE, Faculty of Engineering and Technology, Jain (Deemed-to-be University), Bengaluru, India. He is also the NBA coordinator for the department. He has wide teaching and research experience. Dr. Singh has acquired BTech, MTech, and PhD (IIT Roorkee) in the area of image processing and machine learning. He has authored more than 100 research papers in Scopus and SCIE indexed journals of repute. He has also authored 25 technical books. He is also an associate editor of IEEE Access (SCIE-indexed) and a guest editor of Microprocessors and Microsystems, Wireless Personal Communications, and Complex & Intelligent Systems. He is also a member of the editorial board of Applied Computing and Geoscience (Elsevier). Dr. Singh is an active researcher in the field of Machine Learning, Cognitive Computing, and 6G and beyond networks.

Vibhav Kumar Sachan, PhD
Professor and Additional Head, Department of Electronics and Communication Engineering Department, KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India

VVibhav Kumar Sachan, PhD, is a Professor and Additional Head of the Department of Electronics and Communication Engineering Department at the KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India. Dr. Sachan started his career as a Lecturer of Electronics and Communication Engineering at the KIET Group of Institutions, Ghaziabad, Uttar Pradesh, India. During his academic career of 18 years, Dr. Sachan has taught various subjects at the undergraduate and postgraduate levels and has authored books, edited several conference proceedings, and written book chapters. He has published many papers in reputed international and international journals and conferences. He is on the editorial boards of several international and national journals. Dr. Sachan has received the Dronacharya Award & Letters of Appreciation for his contributions as Additional Head of the Department and Coordinator of Administrative Assignments by the Director General of KIET Group of Institutions, Ghaziabad, and Director of KIET Group of Institutions, Ghaziabad, respectively. Dr. Sachan holds a BTech (with distinction), MTech (with distinction), and PhD degrees. He has been a recipient of merit scholarships throughout his education.

Akansha Singh, PhD
Associate Professor, School of Computer Science Engineering and Technology, Bennett University, India

Akansha Singh, PhD, is working as Associate Professor in the School of Computer Science Engineering and Technology, Bennett University, India. She has to her credit more than 70 research papers, 20 books, and numerous conference papers. She has been the editor for books on emerging topics with publishers like Elsevier, Taylor and Francis, Wiley, etc. Dr. Singh has served as a reviewer and technical committee member for multiple conferences and journals of high repute. She is also an associate editor for the journals IEEE Access and IET Image Processing. She has also served as guest editor for several journals, including Complex and Intelligent Systems, Real Time Imaging, etc. Dr. Singh has also undertaken a government-funded project as principal investigator. Her research areas include image processing, remote sensing, IoT, and machine learning. Dr. Singh has a BTech, MTech, and PhD in Computer Science. She received her PhD from IIT Roorkee in the area of image processing and machine learning.

Sanjeevikumar Padmanaban, PhD
Faculty Member, Department of Energy Technology, Aalborg University, Esbjerg, Denmark

Sanjeevikumar Padmanaban, PhD, is a senior member of IEEE and a faculty member with the Department of Energy Technology, Aalborg University, Esbjerg, Denmark. He is affiilated with CTIF Global Capsule, Department of Business Development and Technology Aarhus University, Herning, Denmark. He was formerly an Associate Professor with VIT University, from 2012 to 2013. He joined the National Institute of Technology, India, as a faculty member. In 2014, he was invited as a Visiting Researcher with the Department of Electrical Engineering, Qatar University, Doha, Qatar, funded by the Qatar National Research Foundation. He continued his research activities with the Dublin Institute of Technology, Ireland, in 2014. Further, he served as an Associate Professor with the Department of Electrical and Electronics Engineering, University of Johannesburg, South Africa, from 2016 to 2018. He received a bachelor’s degree in electrical engineering from the University of Madras, Chennai, India; a master’s degree (Hons.) in electrical engineering from Pondicherry University, Puducherry, India, and a PhD degree in electrical engineering from the University of Bologna, Bologna, Italy.

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