Cognition-based Smart Computing

Nyhet

Foundations, Frameworks, and Applications

Inbunden, Engelska, 2026

AvSangita S. Chaudhari,Pallavi Vijay Chavan,Parikshit Mahalle,Pranav Pawar,Mumbai) S Chaudhari, Sangita (RAIT,Pallavi (DY Patil (Deemed to be Uni.)) Vijay Chavan,Pune) Mahalle, Parikshit (VIIT

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The book guides the smart computing community toward future directions in cognitive research and demonstrates how these advances can be applied to next-generation smart systems. 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 (AI) and its applications in machine self-learning, human-computer interaction, natural language (NL) processing, cognitive models, and architectures.• Discusses machine learning (ML) 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.

Produktinformation

Utgivningsdatum2026-03-31
Mått156 x 234 x undefined mm
FormatInbunden
SpråkEngelska
Antal sidor278
FörlagTaylor & Francis Ltd
ISBN9781032795331

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Elektronik och kommunikationer inom Naturvetenskap och teknik
Programvaruutveckling inom Data och it
Databaser inom Data och it
Systemvetenskap och AI inom Data och it

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 networksecurity 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.

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