Deep Learning Approaches in Intelligent Wireless Networking

Author:   Bharat Bhushan (Sharda University, India) ,  Mohd Anas Wajid ,  Sudhir Kumar Sharma (Institute of Information Technology and Management, India) ,  Achyut Shankar (School of Computer Science Engineering and Technology, Bennett University, Greater Noida, U.P., India)
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032998152


Pages:   310
Publication Date:   30 April 2026
Format:   Hardback
Availability:   In Print   Availability explained
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Deep Learning Approaches in Intelligent Wireless Networking


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Author:   Bharat Bhushan (Sharda University, India) ,  Mohd Anas Wajid ,  Sudhir Kumar Sharma (Institute of Information Technology and Management, India) ,  Achyut Shankar (School of Computer Science Engineering and Technology, Bennett University, Greater Noida, U.P., India)
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.770kg
ISBN:  

9781032998152


ISBN 10:   1032998156
Pages:   310
Publication Date:   30 April 2026
Audience:   College/higher education ,  Professional and scholarly ,  Tertiary & Higher Education ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

Chapter 1. Deep Learning Transformations for Innovating Healthcare in the Health Sector. Chapter 2. Preliminary Study of 6G Networks Signifies A Revolutionary Change in Wireless Communication. Chapter 3. AI Applications, Healthcare, Agriculture, Defence & Medicine. Chapter 4. Artificial intelligence & Machine learning in healthcare: A systematic bibliometric analysis. Chapter 5. Deep Learning and Neural Network in the Stock Market. Chapter 6. Deep Learning Strategies for Advanced Wireless Communication. Chapter 7. A Machine Learning Based Model for Predicting Diabetes Leading to Retinopathy. Chapter 8. Intelligent Wireless Networks: Edge Computing, Sensors, Real-Time Computing, Security, Emerging Applications. Chapter 9. Empowering the Future of Education and Data Science: A Deep Learning Approach to Wireless Networks. Chapter 10. ML Algorithms Supervised/Unsupervised Learning, Application in Diverse Fields Including Networking. Chapter 11. ML in Wireless Networks: Management, Security, Analytics, Virtualization, Sensors, Real Cases

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Author Information

Bharat Bhushan is an Associate Professor at Department of Computer Science and Engineering, Sharda School of Computing Science & Engineering, Sharda University, Greater Noida, India. Mohd Anas Wajid is an Assistant Professor and Post-Doctoral Research Associate at TEC de Monterrey, Mexico. His research interests include Soft Computing, Machine Learning, Data Science, Information Retrieval, Neutrosophy, and STEM. Sudhir Kumar Sharma is currently a Professor at Department of Computer Science & Applications, Sharda School of Computing Science & Engineering, Sharda University, Greater Noida, India His research interests include Artificial Intelligence, LLMs and Security. Achyut Shankar is currently working as an Associate Professor at School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India. His areas of interest include Wireless sensor network, Machine Learning, Internet of things, Block-chain and Cloud computing. Mithun Chakraborty is currently associated with Darjelling Hill Institute of Technology and Management as Founding Principal. His current research focus is intelligent sensing, communication and computing, joint radar communication based smart vehicle. Parma Nand is Dean and Pro-VC at School of Computing Science & Engineering, Sharda University, Greater Noida, India. He has expertise in Wireless and Sensor Network, Cryptography, Algorithm and Computer Graphics.

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