This book delves into the history of biometrics, the different systems that have been developed to date, problems that have arisen from these systems, the necessity of AI-based biometrics systems, different AI techniques developed to date (including machine learning, deep learning, natural language processing, and pattern recognition), their potential uses and applications, security and privacy issues in AI-based Biometric systems, current trends in AI-based biometrics, and presents case studies of AI-based biometrics.

Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data

The healthcare industry has reached its full capacity due to the outbreak of COVID-19. Its global influence has brought attention to the utmost capabilities and limitations of healthcare facilities worldwide. The Internet of Things (IoT) and cloud services can effectively handle the immense healthcare demands that have never been seen before. The scarcity of healthcare personnel and limited resources necessitate the adoption of emerging technology to bolster healthcare delivery. IoT and cloud computing present ample promise in situations like this, as they may be utilized for monitoring, diagnostics, support, and intelligent decision-making. Revolutionizing Healthcare Systems Through Cloud Computing and IoT explores the concepts of cloud computing-based healthcare systems, IoT-based healthcare systems, and cloud-IoT-based healthcare systems. It delves into the significance and benefits of cloud-IoT-based healthcare systems. Covering topics such as disease screening, smart monitoring, and healthcare policy, this book is an excellent resource for researchers, scientists, engineers, graduate and postgraduate students, healthcare professionals and administrators, educators, and more.

This book provides an in-depth overview of artificial intelligence and deep learning approaches with case studies to solve problems associated with biometric security such as authentication, indexing, template protection, spoofing attack detection, ROI detection, gender classification etc. This text highlights a showcase of cutting-edge research on the use of convolution neural networks, autoencoders, recurrent convolutional neural networks in face, hand, iris, gait, fingerprint, vein, and medical biometric traits. It also provides a step-by-step guide to understanding deep learning concepts for biometrics authentication approaches and presents an analysis of biometric images under various environmental conditions. This book is sure to catch the attention of scholars, researchers, practitioners, and technology aspirants who are willing to research in the field of AI and biometric security.

Healthcare professionals face a range of challenges in modern clinical medicine, from managing neurodegenerative disorders like Alzheimer's disease to treating allergic rhinitis in elderly populations. These challenges require innovative solutions, as traditional diagnostic and treatment methods may only sometimes be effective. How can clinicians navigate these challenges and provide the best possible care for their patients? Advancements in Clinical Medicine is a resource that provides practical solutions to these challenges through innovative approaches like machine learning integration and super-resolution reconstruction techniques revolutionize how we approach diagnosis and treatment. By leveraging cutting-edge technologies like artificial intelligence, this book equips scholars and practitioners with the tools they need to tackle even the most daunting medical challenges head-on.

​This book focuses on a wide range of breakthroughs related to digital biometrics and forensics. The authors introduce the concepts, techniques, methods, approaches and trends needed by cybersecurity specialists and educators for keeping current their biometrics and forensics knowledge. Furthermore, the book provides a glimpse of future directions where biometrics and forensics techniques, policies, applications, and theories are headed. Topics include multimodal biometrics, soft biometrics, mobile biometrics, vehicle biometrics, vehicle forensics, integrity verification of digital content, people identification, biometric-based cybercrime investigation, among others. The book is a rich collection of carefully selected and reviewed manuscripts written by diverse digital biometrics and forensics experts in the listed fields and edited by prominent biometrics and forensics researchers and specialists.

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

This book covers current technological innovations and applications in image processing, introducing analysis techniques and describing applications in remote sensing and manufacturing, among others. The authors include new concepts of color space transformation like color interpolation, among others. Also, the concept of Shearlet Transform and Wavelet Transform and their implementation are discussed. The authors include a perspective about concepts and techniques of remote sensing like image mining, geographical, and agricultural resources. The book also includes several applications of human organ biomedical image analysis. In addition, the principle of moving object detection and tracking — including recent trends in moving vehicles and ship detection – is described. Presents developments of current research in various areas of image processing; Includes applications of image processing in remote sensing, astronomy, and manufacturing; Pertains to researchers, academics, students, and practitioners in image processing.

This book is designed to impart and convey knowledge as well as understanding of the range of biometric technologies and cybertechnologies, while also stressing their advantages and disadvantages. The authors develop an appreciation for and breadth of knowledge that spans the full range of neuroscience sub-disciplines, including behavioural, cognitive, and computational neuroscience. Furthermore, the content of the book is geared to be able to place neuroscience into an ethical context, especially showing how studying the brain and behaviour can contribute to the resolution of ethical, social, and environmental issues.