Overview

Integrating Neurocomputing with Artificial Intelligence provides unparalleled insights into the cutting-edge convergence of neuroscience and computing, enriched with real-world case studies and expert analyses that harness the transformative potential of neurocomputing in various disciplines. Integrating Neurocomputing with Artificial Intelligence is a comprehensive volume that delves into the forefront of the neurocomputing landscape, offering a rich tapestry of insights and cutting-edge innovations. This volume unfolds as a carefully curated collection of research, showcasing multidimensional perspectives on the intersection of neuroscience and computing. Readers can expect a deep exploration of fundamental theories, methodologies, and breakthrough applications that span the spectrum of neurocomputing. Throughout the book, readers will find a wealth of case studies and real-world examples that exemplify how neurocomputing is being harnessed to address complex challenges across different disciplines. Experts and researchers in the field contribute their expertise, presenting in-depth analyses, empirical findings, and forward-looking projections. Integrating Neurocomputing with Artificial Intelligence serves as a gateway to this fascinating domain, offering a comprehensive exploration of neurocomputing’s foundations, contemporary developments, ethical considerations, and future trajectories. It embodies a collective endeavor to drive progress and unlock the potential of neurocomputing, setting the stage for a future where artificial intelligence is not merely artificial, but profoundly inspired by the elegance and efficiency of the human brain.

Full Product Details

Author:   Abhishek Kumar (Chandigarh University, Punjab, India) ,  Pramod Singh Rathore (Manipal University Jaipur, India) ,  Sachin Ahuja (Chandigarh University, Punjab, India) ,  Umesh Kumar Lilhore (Galgotias University, Greater Noida, UP, India)
Publisher:   John Wiley & Sons Inc
Imprint:   Wiley-Scrivener
ISBN:  

9781394335688

ISBN 10:   1394335687
Pages:   336
Publication Date:   18 June 2025
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   Awaiting stock  
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Table of Contents

Foreword xiii Preface xv 1 Integrating Fog Computing with AI Model on Decision Making for Distribution of Energy Management 1 Prajwal Hegde N., Parvathi C., Ajay Malpani, D. Suganthi and Priya Batta 2 Construction and Simulation of Hybrid Neural Network and LSTM to Language Process Model Kiran Sree Pokkuluri, Ramakrishna Kolikipogu, K.S. Chakradhar, Rama Devi P. and Mamta 3 An Approach to Ensure the Safety of Industry 4.0 Mobile Robots 33 P. Balaji Srikaanth, Rajeshwari M. Hegde, Ramachandra V. Ballary, Poornachandran R., R. Senthamil Selvan and Amandeep Kaur 4 Feature Extrusion and Categorization of Disease by Hybrid Neuro-Fuzzy Computing 49 Manideep Yenugula, K.S. Chakradhar, Makhan Kumbhkar, D. Victorseelan and Rupinder Karur 5 AI Based Neuromorphic Vision to Control the Robotic Drilling Machine 69 Venkat Namdev Ghodke, Rajeshwari M. Hegde, Ramachandra V. Ballary and R. Senthamil Selvan 6 Design and Development of AI Neuromorphic to Control the Autonomous Driving System 87 J. Balamurugan, Mohammed Mahaboob Basha, Mamatha Bai B. G., J. A. Jevin, Rakesh Bharti and R. Senthamil Selvan 7 Design of Brain-Computer Interface System to Develop Humanoid Robot 105 R. Raffik, K. Senthilkumar, A. Sakira Parveen, K. Akila, B. Sabitha and P. Magudapathi 8 AI-Based Neural Network Used to Enhance the Decision-Making System to Improve Operational Performance 123 G. Naga Rama Devi, Manthena Swapna Kumari, Vijaykumar S. Biradar, Manish Maheshwari, Subramanian Selvakumar and Jenita Subash 9 Simulation and Implementation of English Speech Recognition by NLP 139 K. Kavita, K. Suresh Kumar, Sridevi Dasam and Kiran Sree Pokkuluri 10 Deep Learning-Based Neuro Computing to Classify and Diagnosis of Ophthalmology by OCT 159 D. Arul Pon Daniel, Santhana Sagaya Mary A. and S. Chidambaranathan 11 Deep CNN-Based Multi-Image Steganography: Private Key 175 S. Pavan Kumar Reddy, K. Suresh Kumar, Madhu G.C. and Pavitar Parkash Singh 12 Automatic Classification of Honey Bee Subspecies by AI-Based Neural Network 191 B. Sai Chandana, Ravindra Changala, R. Sivaraman and Anand Bhat B. 13 Acoustic Modeling and Evaluation of Speech Recognition by Neural Networks 207 Y. Ramadevi, K. Suresh Kumar, Venkata Pavankumar and G.N.R. Prasad 14 Brain-Computer Interface for Humanoid Robot Control Adaptation 227 B. Sai Chandana, K.S. Chakradhar, T. Rajasanthosh Kumar and Makhan Kumbhkar 15 Evaluation and Validation of Type 1 Diabetes Clinical Data by GAN 243 Robin Rohit Vincent, Senthilkumar Moorthy, F. Nisha and Soumya 16 Exploring Neuromorphic Computing with Deep Learning: Unveiling Opportunities, Applications, and Overcoming Challenges 261 Yogesh Kumar Sharma, Smitha, Shaik Saddam Hussain and Leena Arya 17 Quantum Neurocomputing: Bridging the Frontiers of Quantum Computing and Neural Networks 287 Smitha, Yogesh Kumar Sharma, Muniraju Naidu Vadlamudi and Leena Arya References 303 Index 307

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Author Information

Abhishek Kumar, PhD is a professor and Assistant Director in the Computer Science and Engineering Department at Chandigarh University, Punjab with over 13 years of teaching experience. He has published over 170 peer-reviewed papers, seven books, and one patent and edited over 50 volumes. His research interests include artificial intelligence, renewable energy systems, image processing, and data mining. Pramod Singh Rathore is an assistant professor in the Department of Computer and Communication Engineering at Manipal University with over 11 years of teaching experience. He has published over 55 papers in reputable national and international journals, books, and conferences. His research interests include NS2, computer networks, mining, and database management systems. Sachin Ahuja, PhD is the Executive Director of Engineering at Chandigarh University with extensive research and academic experience. He has served in key academic positions at various reputed higher education institutes, guiding several master’s and doctoral scholars in areas including artificial intelligence, machine learning, and data mining. Umesh Kumar Lilhore, PhD is affiliated with Galgotias University where he actively engages in academic leadership, research, and mentoring. He has published over 100 scholarly articles and is a senior member of the Institue for Electrical and Electronics Engineers. His areas of expertise include artificial intelligence, machine learning, Internet of Things (IoT), cloud computing, and cybersecurity.

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