Machine Intelligence, Big Data Analytics, and IoT in Image Processing: Practical Applications
- 7h 52m
- Ashok Kumar, Jose A. Galindo, Lalit Garg, Megha Bhushan, Yu-Chen Hu
- John Wiley & Sons (US)
- 2023
MACHINE INTELLIGENCE, BIG DATA ANALYTICS, AND IoT IN IMAGE PROCESSING
Discusses both theoretical and practical aspects of how to harness advanced technologies to develop practical applications such as drone-based surveillance, smart transportation, healthcare, farming solutions, and robotics used in automation.
The concepts of machine intelligence, big data analytics, and the Internet of Things (IoT) continue to improve our lives through various cutting-edge applications such as disease detection in real-time, crop yield prediction, smart parking, and so forth. The transformative effects of these technologies are life-changing because they play an important role in demystifying smart healthcare, plant pathology, and smart city/village planning, design and development. This book presents a cross-disciplinary perspective on the practical applications of machine intelligence, big data analytics, and IoT by compiling cutting-edge research and insights from researchers, academicians, and practitioners worldwide. It identifies and discusses various advanced technologies, such as artificial intelligence, machine learning, IoT, image processing, network security, cloud computing, and sensors, to provide effective solutions to the lifestyle challenges faced by humankind.
Machine Intelligence, Big Data Analytics, and IoT in Image Processing is a significant addition to the body of knowledge on practical applications emerging from machine intelligence, big data analytics, and IoT. The chapters deal with specific areas of applications of these technologies. This deliberate choice of covering a diversity of fields was to emphasize the applications of these technologies in almost every contemporary aspect of real life to assist working in different sectors by understanding and exploiting the strategic opportunities offered by these technologies.
Audience
The book will be of interest to a range of researchers and scientists in artificial intelligence who work on practical applications using machine learning, big data analytics, natural language processing, pattern recognition, and IoT by analyzing images. Software developers, industry specialists, and policymakers in medicine, agriculture, smart cities development, transportation, etc. will find this book exceedingly useful.
About the Author
Ashok Kumar, PhD, is an assistant professor at Lovely Professional University, Phagwara, Punjab, India. He has 15+ years of teaching and research experience, filed 3 patents, and published many articles in international journals and conferences. His current areas of research interest include cloud computing, the Internet of Things, and mist computing.
Megha Bhushan, PhD, is an assistant professor at the School of Computing, DIT University, Dehradun, Uttarakhand, India. She has filed 4 patents and published many research articles in international journals and conferences. Her research interest includes software quality, software reuse, ontologies, artificial intelligence, and expert systems.
Jose Galindo, PhD, is currently in the Department of Computer Languages and Systems, University of Seville, Spain. He has developed many tools such as FaMa, FaMaDEB, FaMaOVM, TESALIA, and VIVID, and his research interests include recommender systems, software visualization, variability-intensive systems, and software product lines.
Lalit Garg, PhD, is a Senior Lecturer in the Department of Computer Information Systems, University of Malta, and an honorary lecturer at the University of Liverpool, UK. He has edited four books and published over 110 papers in refereed journals, conferences, and books. He has 12 patents and delivered more than twenty keynote speeches in different countries, and organized/chaired/co-chaired many international conferences.
Yu-Chen Hu, PhD, is a distinguished professor in the Department of Computer Science and Information Management, Providence University, Taichung City, Taiwan. His research interests include image and signal processing, data compression, information hiding, information security, computer network, and artificial network.
In this Book
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Deep Learning Techniques using Transfer Learning for Classification of Alzheimer's Disease
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Medical Image Analysis of Lung Cancer CT Scans Using Deep Learning with Swarm Optimization Techniques
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Liver Cancer Classification with using Gray-Level Co-Occurrence Matrix using Deep Learning Techniques
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Transforming the Technologies for Resilient and Digital Future during COVID-19 Pandemic
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Plant Pathology Detection using Deep Learning
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Smart Irrigation and Cultivation Recommendation System for Precision Agriculture Driven by IoT
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Machine Learning-Based Hybrid Model for Wheat Yield Prediction
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A Status Quo of Machine Learning Algorithms in Smart Agricultural Systems Employing IoT-Based WSN—Trends, Challenges and Futuristic Competences
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Impact of Data Pre-Processing in Information Retrieval for Data Analytics
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Cloud Computing Security, Risk, and Challenges—A Detailed Analysis of Preventive Measures and Applications
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Internet of Drone Things—A New Age Invention
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Computer Vision-Oriented Gesture Recognition System for Real-Time ISL Prediction
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Recent Advances in Intelligent Transportation Systems in India—Analysis, Applications, Challenges, and Future Work
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Evolutionary Approaches in Navigation Systems for Road Transportation System
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IoT-Based Smart Parking System for Indian Smart Cities
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Security of Smart Home Solution Based on Secure Piggybacked Key Exchange Mechanism
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Machine Learning Models in Prediction of Strength Parameters of FRP-Wrapped RC Beams
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Prediction of Indoor Air Quality using Artificial Intelligence
