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-solving.
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-solving. Drawing inspiration from human cognition, intelligent computing (IC) integrates AI techniques such as machine learning, neural networks, deep learning, evolutionary algorithms, and swarm intelligence to build adaptive, efficient, and autonomous systems. These technologies are now at the heart of innovations across disciplines – from robotics and natural language processing to agriculture, medicine, and economics. This book presents a comprehensive view of the latest advancements in intelligent computing, offering both foundational knowledge and practical insights. It is designed to serve as a valuable resource for students, researchers, and professionals seeking to understand and apply IC techniques in real-world scenarios.
- Showcases recent, impactful applications of intelligent computing across diverse domains, supported by detailed case studies.
- Offers deep insights into the latest research developments and outlines promising areas for future exploration in intelligent computing.
- Combines theoretical foundations with algorithmic, simulation-based, and implementation-oriented research to provide a holistic understanding of IC systems.
- Balances foundational theory for beginners with practical simulations and real-life implementations for intermediate and advanced readers.
1. A Review on Global Land Use/Land Cover Change Analysis Using Digital
Image Processing,
2. Reduction of Two-Dimensional Data for Speeding Up Convex
Hull Computation,
3. Enhancing Brain Tumor Detection with an Ensemble Model,
4. Optical Character Recognition-Based Intelligent Grading System for
Handwritten Text,
5. Quantum-Inspired Neural Networks: Bridging Quantum
Computing and Deep Learning for Next-Generation AI Systems,
6. Deep
Learning-Based Approach for Robust Image Authentication,
7. AI-Driven
Autonomous Cyber Threat Intelligence (CTI) Curation and Lifecycle Management,
8. Robust Brain Tumor Classification Using Convolutional Neural Networks for
Enhanced Diagnostics,
9. Real-Time Feedback for Teachers Using Multi-Modal
Emotion Detection in Classroom Teaching,
10. Enhanced Approach for Chronic
Disease Diagnosis and Prediction Using Ensemble Deep Learning,
11. Empowering
Industry 5.0 with Large Language Models for Phishing Defense,
12.
AI-Generated Text Detection: A Hybrid CNN-BiLSTM and BERT-Based Large
Language Model Approach,
13. Resource-Aware Arabic LLM Creation: Model
Adaptation, Integration, and Multi-Domain Testing,
14. Classification of
Sleep Stage for Human Wellness from Single-Channel EEG Using Convolutional
Neural Network of Deep Learning,
15. Maximizing Minimum Flow Rates Using
Graph Conversion Techniques in Rechargeable Wireless Sensor Networks (rWSN),
16. Explainable Transformer-Augmented U-Net for Brain Tumor Segmentation in
MRI,
17. CycleGAN-Based MRI-to-CT Image Synthesis for Tumor-Centric Medical
Image Translation,
18. Preprocessing in Colorectal Cancer Histopathology: A
Prerequisite for Effective Computational Analysis,
19. CBI4EADP: CatBoost
Integrated Early Alzheimers Disease Prediction Model Using EHRs,
20.
Evolutionary Algorithms versus Quantum-Inspired Techniques: Theory,
Implementation, and Comparative Insight,
21. Learning Biomedical Associations
from Graph Structures for Next-Generation Digital Health Systems,
22.
Autonomous NLP Agents for Complex Tasks Using Memory Augmentation and
External Tool Reasoning,
23. Improving Transparency and Adaptability in AI
with Hybrid Generative Adversary Attention Networks,
24. Revolutionizing
Swarm Intelligence with Quantum Artificial Intelligence and IoT Technologies,
25. A Bio-Inspired Game Theoretic and AI-Enhanced Approach for Efficient Data
Transfer in Wireless Sensor Networks
Anshul Verma received his M.Tech. and Ph.D. degrees in Computer Science and Engineering from ABVIndian 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.
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