Smart Technologies and Intelligent Computing
CRC Press (Verlag)
978-1-041-12853-3 (ISBN)
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It brings together innovative insights and practical solutions in diverse domains such as Smart Technologies, Intelligent Computing, Artificial Intelligence, Machine Learning, Internet of Things (IoT), Cloud Computing, Big Data Analytics, Advanced Networking Solutions, System Design and Methodologies, and ICT for Sustainability. With novel approaches and real-world applications, this collection of peer-reviewed papers aims to address emerging challenges in smart and intelligent systems.
This volume serves as a valuable resource for researchers, academicians, industry professionals, and students in the fields of Computer Science, Artificial Intelligence, Smart Systems, and Multidisciplinary Technologies. It aims to inspire collaboration and knowledge exchange among academia and industry, fostering innovation that drives the future of sustainable computing.
Jaskaran Singh, Dean Research and Head of the School of Forensic Science at Geeta University, Panipat, is an accomplished academic and researcher. An INSPIRE Fellow (DST, India) and Gold Medalist in Forensic Science, he has guided multiple Ph.D. and master’s scholars. Dr. Singh has published over 35 research papers in reputed Scopus and ABDC-indexed journals, authored five books, and holds 25 patents, including three granted. A motivational speaker and international trainer, he has delivered over 100 workshops, conferences, and expert sessions across India and abroad, contributing significantly to research, training, and knowledge dissemination. Meenu Gupta (Stanford’s Top 2% Scientists, 2025) is a Professor and Head of Conferences & Research Outreach (Engineering Cluster) in the UIE-CSE Department at Chandigarh University, India. She is currently pursuing her Postdoctoral Fellowship at the MIR Lab, USA, and holds a Ph.D. in Computer Science and Engineering from Ansal University, Gurgaon (2020). With over 17 years of teaching and research experience, her expertise spans Machine Learning, Intelligent Systems, Data Mining, Artificial Intelligence, Image Processing, Smart Cities, Data Analysis, and Brain–Machine Interaction (BMI). Dr. Gupta has edited 22+ books and authored four engineering books. She has published over 250 research papers in reputed international journals and conferences, along with 45+ book chapters. She actively serves as a reviewer for several high-impact journals, including Big Data, Artificial Intelligence Review, Scientific Reports, CMC, and Digital Health. She is a Senior Member of IEEE, Life Member of ISTE and IAENG, and currently an Executive Committee Member of IEEE Delhi Section as well as Advisor of the IEEE RAS Chapter. She has also organized numerous conferences technically sponsored by IEEE Delhi Section, IEEE CIS, AIP, and others, contributing significantly to advancing research outreach and collaborations. Rakesh Kumar is an Associate Director at the UIE-CSE Department, Chandigarh University, Punjab, India. He is pursuing his Post Doc Fellowship from MIR lab, USA. He has completed his Ph.D. in Computer Science and Engineering from Punjab Technical University, Jalandhar, 2017. He has more than 22 years of teaching experience. His research interests are IoT, Machine Learning, and Natural Language Processing. He has edited over 12 books with reputed publishers and has authored five books. He works as a reviewer for several journals, including Big Data, CMC, Scientific Reports, TSP, Multimedia Tools and Applications, IEEE Access, etc. He is a Senior Member of IEEE. He has authored or co-authored more than 200 publications in various national/ international conferences and journals. He is also an organiser and editor of many international conferences under the aegis of IEEE and AIP.
1. Optimizing Text Classification: Particle Swarm Approach to Random Forests 2. Deep Learning Approaches for Reliable Object Detection Under Adverse Weather 3. IoT Based Water Pipeline Leakage Detection 4. Handwritten Examination Evaluation using LLMs and GenAI 5. Deep Retinex-Inspired Enhancement of Low-Light Lunar Images Using Dark-Bright Image Pairs 6. Solar Irradiation Component Forecasting Using ANN Framework with Diverse Configuration of Meteorological Parameters 7. Quantum-Enhanced Machine Learning for Predictive Catalysis: A Unified Framework for Transition Metal Complex Activity Forecasting
| Erscheint lt. Verlag | 12.3.2026 |
|---|---|
| Verlagsort | London |
| Sprache | englisch |
| Maße | 174 x 246 mm |
| Themenwelt | Informatik ► Weitere Themen ► CAD-Programme |
| Technik ► Elektrotechnik / Energietechnik | |
| ISBN-10 | 1-041-12853-3 / 1041128533 |
| ISBN-13 | 978-1-041-12853-3 / 9781041128533 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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