1st Edition

Research Advances in Intelligent Computing Volume 3

Edited By Anshul Verma, Pradeepika Verma Copyright 2026
464 Pages 252 B/W Illustrations
by CRC Press

464 Pages 252 B/W Illustrations
by CRC Press

As computers and intelligent machines evolve at an unprecedented pace, the quest to replicate human intelligence in software and systems has become a defining challenge of our time. Research Advances in Intelligent Computing: Volume 3 explores this dynamic field, where artificial intelligence (AI) and computational models converge to create systems capable of learning, reasoning, and problem... Read more

Preface
Editor Biographies
Contributors
Acknowledgments

1. A Review on Global Land Use/Land Cover Change Analysis Using Digital Image Processing
B. G. Kodge, Abhijit Patil, and Raghavendra Kulkarni

2. Reduction of Two-Dimensional Data for Speeding Up Convex Hull Computation
Debashis Mukherjee

3. Enhancing Brain Tumor Detection with an Ensemble Model
Sushopti Gawade, Aditya Uttam Desai, Ruwayd Hussain Charfare, and Nishad Nitin Keni

4. Optical Character Recognition-Based Intelligent Grading System for Handwritten Text
Hasmita Patnana, Roshni Joshi, Tanya Dora, and Prabakaran N.

5. Quantum-Inspired Neural Networks: Bridging Quantum Computing and Deep Learning for Next-Generation AI Systems
R. Raihana Parveen, N. S. Kalyan Chakravarthy, S. Jafar Ali Ibrahim, Raenu Kolandaisamy, Janga Srinivasa Rao, and Y. V. Hanumantha Rao

6. Deep Learning-Based Approach for Robust Image Authentication
Vasudeva Pai, Nagendra Pai, Nishanth D. Shetty, and Raghavendra S. Shettigar

7. AI-Driven Autonomous Cyber Threat Intelligence (CTI) Curation and Lifecycle Management
Shubham Gupta

8. Robust Brain Tumor Classification Using Convolutional Neural Networks for Enhanced Diagnostics
Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, and Prince L.

9. Real-Time Feedback for Teachers Using Multi-Modal Emotion Detection in Classroom Teaching
A. Annapurna, P. Kiran Rao, B. Bhaskara Rao, and P. Penchal Prasad

10. Enhanced Approach for Chronic Disease Diagnosis and Prediction Using Ensemble Deep Learning
Tamilarasi Kathirvel Murugan, Logeswari Govindaraj, Divyansh Chawla, Shivin Mangal, and Shakti Nayak

11. Empowering Industry 5.0 with Large Language Models for Phishing Defense
Piyush Kumar Ghosh, Aditya Bhushan, Dharmendra Kumar, and Ashutosh Kumar Singh

12. AI-Generated Text Detection: A Hybrid CNN-BiLSTM and BERT-Based Large Language Model Approach
Manish Prajapati and Santos Kumar Baliarsingh

13. Resource-Aware Arabic LLM Creation: Model Adaptation, Integration, and Multi-Domain Testing
Prakash Aryan

14. Classification of Sleep Stage for Human Wellness from Single-Channel EEG Using Convolutional Neural Network of Deep Learning
Kumari Nidhi Lal, Richa Agrawal, and Shubham Agarwal

15. Maximizing Minimum Flow Rates Using Graph Conversion Techniques in Rechargeable Wireless Sensor Networks (rWSN)
Shishupal Kumar and Kumari Nidhi Lal

16. Explainable Transformer-Augmented U-Net for Brain Tumor Segmentation in MRI
Hariharan Ramamoorthy, Dhilsath Fathima M., Rajalakshmi V., and Aarya A.

17. CycleGAN-Based MRI-to-CT Image Synthesis for Tumor-Centric Medical Image Translation
Poornima Devi M., N. Vinothini, and S. Priyadharshini

18. Preprocessing in Colorectal Cancer Histopathology: A Prerequisite for Effective Computational Analysis
Sanjeev Kumar and Pramod Kumar Mishra

19. CBI4EADP: CatBoost Integrated Early Alzheimer’s Disease Prediction Model Using EHRs
Kanak Kumar, Anshul Verma, and Pradeepika Verma

20. Evolutionary Algorithms versus Quantum-Inspired Techniques: Theory, Implementation, and Comparative Insight
Pawan Mishra and Anushka Prajapati

21. Learning Biomedical Associations from Graph Structures for Next-Generation Digital Health Systems
Ronalda M. and Roohie Naaz Mir

22. Autonomous NLP Agents for Complex Tasks Using Memory Augmentation and External Tool Reasoning
Himanshu Shekhar, P. V. Rajlakshmi, Prem Kumar Sholapurapu, Venkatesh Kumar C., L. Bhagyalakshmi, and Sanjay Kumar Suman

23. Improving Transparency and Adaptability in AI with Hybrid Generative Adversary Attention Networks
Kumaresh Sheelavant, Lakshmi Chandrakanth Kasireddy, Nelli Sreevidya, V. Arunkumar, L. Jayanthi, and Hitha Poddar

24. Revolutionizing Swarm Intelligence with Quantum Artificial Intelligence and IoT Technologies
Akshay Varkele, Aishwarya Mishra, Vishal Mehra, and Poonam Khatarkar

25. A Bio-Inspired Game Theoretic and AI-Enhanced Approach for Efficient Data Transfer in Wireless Sensor Networks
Prinsi Sahpuriya, Indra Kumar Sanodiya, Damini Singh, and Aakansha Verma

Biography

Anshul Verma received his M.Tech. and Ph.D. degrees in Computer Science and Engineering from ABV–Indian Institute of Information Technology and Management (IIITM), Gwalior, India. He pursued his postdoctoral research at the Indian Institute of Technology (IIT) Kharagpur, India. He is currently serving as an Assistant Professor in the Department of Computer Science, Institute of Science, Banaras Hindu University (BHU), Varanasi, India, with over 10 years of academic and research experience. Prior to joining BHU, he was associated with the Department of Computer Science and Engineering at Motilal Nehru National Institute of Technology (MNNIT) Allahabad and the National Institute of Technology (NIT) Jamshedpur as a faculty member. His research interests span Cloud Computing, Distributed Systems, Mobile Ad-hoc Networks, and Formal Verification. He has successfully organized four editions of the International Conference on Advanced Network Technologies and Intelligent Computing (ANTIC) as General Chair and Convener since 2021. He has published extensively in renowned journals, books, and conferences. He is currently leading three externally funded and three institutionally funded research projects as Principal Investigator/Co-Principal Investigator. He also contributes actively to the academic publishing community, serving as an Associate Editor of the Journal of Scientific Research of the Banaras Hindu University and as an Editorial Board Member of Scientific Reports of Springer.


Pradeepika Verma received her Ph.D. degree in Computer Science and Engineering from the Indian Institute of Technology (ISM) Dhanbad, India. She has received M.Tech in Computer Science and Engineering from Banasthali University, Rajasthan, India. Currently, she is working as a Faculty Fellow in Technical Innovation Hub at Indian Institute of Technology, Patna, India. She has worked as a Post-Doctoral Fellow in Department of Computer Science and Engineering at Indian Institute of Technology (BHU), Varanasi, India. She has also worked as an Assistant Professor in the Department of Computer Science and Engineering at Pranveer Singh Institute of Technology, Kanpur, India, and as a Faculty Member in the Department of Computer Application at the Institute of Engineering and Technology, Lucknow, India. Her current research interests include Natural Language Processing, Optimization Approaches, Artificial Intelligence, Cloud Computing, and Distributed Systems.