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Computation intelligence (CI) paradigms, including artificial neural networks, fuzzy systems, evolutionary computing techniques, and intelligent agents, form the basis of making clinical decisions. This book explains different aspects of the current research on CI technologies applied in the field of medical diagnosis. It discusses critical issues related to medical diagnosis, like uncertainties in the medical domain, problems in the medical data, especially dealing with time-stamped data, and knowledge acquisition. Features: Introduces recent applications of new computational intelligence technologies focusing on medical diagnosis issues. Reviews multidisciplinary research in health care, l...
This book gathers selected papers presented at the 7th International Conference on Innovations in Electronics and Communication Engineering, held at Guru Nanak Institutions in Hyderabad, India. It highlights contributions by researchers, technocrats and experts regarding the latest technologies in electronic and communication engineering, and addresses various aspects of communication engineering, including signal processing, VLSI design, embedded systems, wireless communications, and electronics and communications in general. Covering cutting-edge technologies, the book offers a valuable resource, especially for young researchers.
This book covers computer vision-based applications in digital healthcare industry 4.0, including different computer vision techniques, image classification, image segmentations, and object detection. Various application case studies from domains such as science, engineering, and social networking are introduced, along with their architecture and how they leverage various technologies, such as edge computing and cloud computing. It also covers applications of computer vision in tumor detection, cancer detection, combating COVID-19, and patient monitoring. Features: Provides a state-of-the-art computer vision application in the digital health care industry Reviews advances in computer vision ...
As society transitions into the digital age, the demand for advanced robotics and autonomous systems has remained unchanged. However, the field faces significant challenges bridging the gap between current capabilities and the potential for brilliant, autonomous machines. While exact and efficient, current robotic systems need more sophistication and adaptability of human intelligence. This limitation restricts their application in complex and dynamic environments, hindering their ability to realize their potential fully. Multidisciplinary Applications of AI Robotics and Autonomous Systems addresses these challenges by presenting cutting-edge research and innovative robotics and autonomous systems solutions. By exploring topics such as digital transformation, IoT, AI, and cloud-native computing paradigms, readers will understand the latest advancements in the field. The book delves into theoretical frameworks, computational models, and experimental approaches, offering insights to help researchers and practitioners develop more intelligent and autonomous machines.
This edited book presents an insight for modelling, procuring, and building the smart city plan using the Internet of Things (IoT) and a security framework using blockchain technology. The applications of Li-Fi and 5G in smart cities are included, along with their implementation, challenges, and advantages. This book focuses on the use of IoT and blockchain in the day-to-day transparent and recorded activities of citizens of smart cities like, smart citizen management. The future for upgrading the system as per technological advancements is also discussed. This book: integrates IoT, blockchain, Li-Fi, and 5G in smart city implementation covers smart supply chain management using IoT outlines the state-of-the-art and sustainable implementation of smart cities and practical challenges includes sustainable development of smart cities presents detailed explanation of case studies of smart cities of developed countries and developing countries and their comparisons This book is aimed at researchers and graduate students in Artificial Intelligence, Urban Planning, and Information Technology Systems and Management.
This book discusses state-of-the-art reviews of the existing machine learning techniques and algorithms including hybridizations and optimizations. It covers applications of machine learning via artificial intelligence (AI) prediction tools, discovery of drugs, neuroscience, diagnosis in multiple imaging modalities, pattern recognition approaches to functional magnetic resonance imaging, image and speech recognition, automatic language translation, medical diagnostic, stock market prediction, traffic prediction, and product automation. Features: • Focuses on hybridization and optimization of machine learning techniques. • Reviews supervised, unsupervised, and reinforcement learning using...
Intelligent Techniques for Cyber-Physical Systems covers challenges, opportunities, and open research directions for cyber-physical systems (CPS). It focuses on the design and development of machine learning and metaheuristics-enabled methods as well as blockchain for various challenges like security, resource management, computation offloading, trust management, and others in edge, fog, and cloud computing, Internet of Things (IoT), Internet of Everything (IoE), and smart cities. It also includes the design and analysis of deep learning-based models, sensing technologies, metaheuristics, and blockchain for complex real-life systems for CPS. Offers perspectives on the research directions in ...
This new volume introduces various VLSI (very-large-scale integration) architecture for DSP filters, speech filters, and image filters, detailing their key applications and discussing different aspects and technologies used in VLSI design, models and architectures, and more. The volume explores the major challenges with the aim to develop real-time hardware architecture designs that are compact and accurate. It provides useful research in the field of computer arithmetic and can be applied for various arithmetic circuits, for their digital implementation schemes, and for performance considerations.
This book primarily aims to provide an in-depth understanding of recent advances in big data computing technologies, methodologies, and applications along with introductory details of big data computing models such as Apache Hadoop, MapReduce, Hive, Pig, Mahout in-memory storage systems, NoSQL databases, and big data streaming services such as Apache Spark, Kafka, and so forth. It also covers developments in big data computing applications such as machine learning, deep learning, graph processing, and many others. Features: Provides comprehensive analysis of advanced aspects of big data challenges and enabling technologies. Explains computing models using real-world examples and dataset-based experiments. Includes case studies, quality diagrams, and demonstrations in each chapter. Describes modifications and optimization of existing technologies along with the novel big data computing models. Explores references to machine learning, deep learning, and graph processing. This book is aimed at graduate students and researchers in high-performance computing, data mining, knowledge discovery, and distributed computing.
This book provides a framework for robust and novel biometric techniques, along with implementation and design strategies. The theory, principles, pragmatic and modern methods, and future directions of biometrics are presented, along with in-depth coverage of biometric applications in driverless cars, automated and AI-based systems, IoT, and wearable devices. Additional coverage includes computer vision and pattern recognition, cybersecurity, cognitive computing, soft biometrics, and the social impact of biometric technology. The book will be a valuable reference for researchers, faculty, and practicing professionals working in biometrics and related fields, such as image processing, computer vision, and artificial intelligence. Highlights robust and novel biometrics techniques Provides implementation strategies and future research directions in the field of biometrics Includes case studies and emerging applications