The text discusses the fundamentals, frameworks, and practical applications of cognitive and smart computing in diverse areas such as vision and image processing, healthcare, and smart agriculture. It further covers topics such as cognitive modeling, meta-cognition, pattern recognition, and natural language processing.
The book provides a vision to the smart computing community on the future trends in cognition and its applicability in smart computing. It further identifies applications that demonstrate innovative ways of utilizing cognition-based smart computing for solving various real-world problems.
• Presents cognitive modeling in machine consciousness and human cognition.
• Covers artificial intelligence and its applications in machine self-learning, human-computer interaction, natural language processing, cognitive models, and architectures.
• Discusses machine learning and cognitive computing for mobile communications, and wireless networks.
• Explains the foundation, framework, and applications of cognition-based smart computing in a single volume.
• Showcases key issues and challenges in the emerging area of cognitive computation and promotes an interdisciplinary understanding of the diversity in the adaptation of cognition in smart computing.
The text is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
1. AI-Driven Optimization of Multi-Objective Task Scheduling in
Fog-Assisted IoT Environments
2. Transforming Healthcare through Cognitive
Computing and Smart Computing: A Comprehensive Overview
3. Cognitive
Cybersecurity: Symbolic Deep Learning for Enhanced Decision Support
4. Can
Neural Networks Dream? Applying Crick and Mitchison theory of Reorganization
to Multi-Layer Perceptrons for reduction of Catastrophic Interference
5.
Amalgamation of Threat Intelligence for Cognitive Ransomware Detection in 5G
Networks
6. Generative AI Algorithms and Techniques for Cognitive
Computation: A Comprehensive Study
7. Enhancing Object Recognition with YOLO
and OCR Fusion: Towards Intelligent Cognitive Tasks
8. Cognitive Robots for
Industry 5.0 - Fundamentals, Challenges and Research Trends
9. Industry 5.0
Unveiled, Precision Agriculture Empowered: Integrating Recommendation and
Prediction Systems for Transparent Farming Transactions
10. Cognitive
Computing in Banking and Finance
11. Investigating the Role of Large Language
Models in Cognitive Computing
12. Electroencephalogram Feature Extraction
Methods for Stress Analysis
Sangita Chaudhari is currently working as a professor and Head in the Department of Computer Science and Engineering at Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Navi Mumbai, India. She has published papers in International/National Journals/Conferences and book chapters in the domain of information security, image processing, and pattern recognition. Her research interests include image processing, information security, geographical information systems, and remote sensing.
Pallavi Vijay Chavan is presentlyworking as Professor in Department of Computer Engineering, Mukesh Patel School of Technology Management and Engineering, NMIMS University, Mumbai, India. She has 22 years of academic experience in data science and network security In her academic journey, she published research work in the data science and security domain. She has published research papers in journals and conferences of national and international repute.
Parikshit Mahalle is a senior member of IEEE and a Professor, Dean of Research and Development, and Head, of the Department of Artificial Intelligence and Data Science, at Vishwakarma Institute of Information Technology, Pune, India. He completed his Ph. D from Aalborg University, Denmark, and continued as a postdoc researcher at CMI, Copenhagen, Denmark. He has 12 patents, published more than two hundred research papers in journals and conferences of national and international repute. His research interests are machine learning, data science, algorithms, the Internet of Things, identity management, and security.
Pranav Mothabhau Pawar is currently working as an assistant professor, in the Department of Computer Science, at Birla Institute of Technology and Science, Dubai. He developed a deep Q-learning-based asymptotically optimal solution to the spectrum collaboration problem. He published more than 40 papers in national and international journals and conferences.
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