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Books in Computer science

The Computing collection presents a range of foundational and applied content across computer and data science, including fields such as Artificial Intelligence; Computational Modelling; Computer Networks, Computer Organization & Architecture, Computer Vision & Pattern Recognition, Data Management; Embedded Systems & Computer Engineering; HCI/User Interface Design; Information Security; Machine Learning; Network Security; Software Engineering.

    • Feature Extraction and Image Processing for Computer Vision

      • 5th Edition
      • September 22, 2025
      • Mark Nixon + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 6 6 8 6 4
      • eBook
        9 7 8 0 4 4 3 3 6 6 8 7 1
      Feature Extraction and Image Processing for Computer Vision, Fifth Edition is an essential guide to the implementation of image processing and computer vision techniques, with tutorial introductions and sample code in MATLAB and Python. Algorithms are presented and fully explained to enable complete understanding of the methods and techniques demonstrated, providing a link between theory and implementation. Essential background theory is carefully explained. This text gives students and researchers in image processing and computer vision a complete introduction to classic and state-of-the art methods in feature extraction together with practical guidance on their implementation.
    • Advances in Image Processing, Reliability, and Artificial Intelligence

      • 1st Edition
      • November 16, 2025
      • Mario J. Divan + 4 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 4 2 6 6 0
      • eBook
        9 7 8 0 4 4 3 3 4 2 6 7 7
      Advances in Image Processing, Reliability, and Artificial Intelligence: Data Centred-Techniques and Applications in Edge Computing provides a clear outlook of the mechanisms, risks, challenges, and opportunities in system reliability for image processing and AI applications running on edge devices. It provides Best Known Configuration (BKC) and Methods (BKM) while discussing trends and future works based on current research. The content serves as a reference for practitioners and provides a state-of-the-art for researchers in the area. It provides foundations to analyse and replicate different applications through use cases. It tackles concerns for how reliability aspects (i.e., fault tolerance, availability, maturity, and recoverability) are addressed for applications running in an environment that is not fully controlled and exposed to environmental variations.
    • Foundations of Cloud Computing

      • 1st Edition
      • October 1, 2025
      • Robert Shimonski
      • English
      • Paperback
        9 7 8 0 4 4 3 2 1 4 7 9 0
      • eBook
        9 7 8 0 4 4 3 2 1 4 8 1 3
      Foundations of Cloud Computing provides readers with a guidebook to navigating the field of Cloud Computing, including the guiding principles, key concepts, history, terminology, state-of-the-art in research, and a roadmap to where the field intersects and interacts with related fields of research and development. In this age of total connectivity, researchers need to be able to communicate and collaborate with a wide range of colleagues across multiple disciplines. This book helps researchers from all fields understand what Cloud Computing is, how it works, and how to speak the language of collaboration with developers and researchers who specialize in the field. With a complete and in-depth foundation in the key concepts of the field, and a roadmap to where and how Cloud Computing intersects across the domains of scientific research and application development, this book gives readers everything they need to navigate and apply this important, ubiquitous technology.
    • Data-Driven Diagnostics and Disease Prediction with AI Optimization

      • 1st Edition
      • October 1, 2025
      • Shailendra Pratap Singh + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 7 4 7 5
      • eBook
        9 7 8 0 4 4 3 2 6 7 4 8 2
      Data-Driven Diagnostics and Disease Prediction with AI Optimization provides useful insights into model creation, data preparation, and ethical issues for healthcare applications. The book covers all the conventional and non-conventional methods related to this domain. It also discusses AI-based optimization techniques, Machine Learning models, and Advanced AI, offering practical insights, case studies, and optimization strategies to help data scientists and researchers efficiently employ AI in diagnostics and illness prediction in a world where precise diagnostics and early illness prediction may save lives and healthcare resources.
    • Multimodal Learning Using Heterogeneous Data

      • 1st Edition
      • November 1, 2025
      • Saeid Eslamian + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 7 5 2 8 9
      • eBook
        9 7 8 0 4 4 3 2 7 5 2 9 6
      Multimodal Learning Using Heterogeneous Data is a comprehensive guide to the emerging field of multimodal learning, which focuses on integrating diverse data types such as text, images, and audio within a unified framework. The book delves into the challenges and opportunities presented by multimodal data and offers insights into the foundations, techniques, and applications of this interdisciplinary approach. It is intended for researchers and practitioners interested in learning more about multimodal learning and is a valuable resource for those working on projects involving data analysis from multiple modalities.The book begins with a comprehensive introduction, focusing on multimodal learning's foundational principles and the intricacies of heterogeneous data. It then delves into feature extraction, fusion techniques, and deep learning architectures tailored for multimodal data. It also covers transfer learning, pre-processing challenges, and cross-modal information retrieval. The book highlights the application of multimodal learning in specialized contexts such as sentiment analysis, data generation, medical imaging, and ethical considerations. Real-world case studies are woven into the narrative, illuminating the applications of multimodal learning in diverse domains such as natural language processing, multimedia content analysis, autonomous systems, and cognitive computing. The book concludes with an insightful exploration of multimodal data analytics across social media, surveillance, user behavior, and a forward-looking examination of future trends and practical implementations. As a collective resource, Multimodal Learning Using Heterogeneous Data illuminates the powerful utility of multimodal learning to elevate machine learning tasks while also highlighting the need for innovative solutions and methodologies. The book acknowledges the challenges associated with deep learning and the growing importance of ethical considerations in the collection and analysis of multimodal data.Overall, Multimodal Learning Using Heterogeneous Data provides an expansive panorama of this rapidly evolving field, its potential for future research and application, and its vital role in shaping machine learning's evolution.
    • Decision Systems

      • 1st Edition
      • July 9, 2025
      • Pallavi Vijay Chavan + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 3 7 2 8 4
      • eBook
        9 7 8 0 4 4 3 3 3 7 2 9 1
      Decision-making is a fundamental process that influences outcomes across a wide range of domains, including business, healthcare, scientific research, and automation. With the increasing availability of data and the growing computational power of modern systems, decision-making models have become more sophisticated and capable of providing highly accurate and efficient solutions. The ability to develop, analyze, and implement these models has become crucial for professionals and researchers working in fields that rely on data-driven decision-making.This book explores the evolution and significance of decision systems, covering both foundational theories and advanced methodologies. It introduces readers to the essential principles of decision-making models, illustrating their applications through practical case studies and real-world scenarios. The discussion begins with a focus on traditional decision-making techniques and gradually progresses to more advanced topics, including machine learning-based approaches, the integration of artificial intelligence, and the role of fuzzy logic in decision support systems. Furthermore, ethical considerations in decision-making and strategies for mitigating bias are examined, ensuring that models remain fair and transparent.Througho... this book, each chapter builds on the previous one, providing a structured and comprehensive learning experience. By the time readers complete this book, they will have gained an in-depth understanding of decision-making frameworks, their applications, and the future directions of research in this dynamic field. Whether one is a student, a researcher, or an industry professional, this book serves as a valuable guide to mastering the complexities of decision systems and applying them effectively in various domains.
    • Video Health Monitoring in Hospitals

      • 1st Edition
      • November 1, 2025
      • Wenjin Wang + 3 more
      • English
      • Paperback
        9 7 8 0 4 4 3 2 6 5 8 6 0
      • eBook
        9 7 8 0 4 4 3 2 6 5 8 7 7
      Video Health Monitoring in Hospitals discusses the emergence of camera-based, contactless physiological measurement as a groundbreaking solution in healthcare monitoring. The book highlights the technology's non-invasiveness, capacity for continuous and long-term monitoring, and its ability to capture not only vital signs but also contextual information and behaviors. A unique aspect of this book is its rich set of compelling healthcare applications that will attract broader audiences (including researchers, engineers, clinicians, and students) from multidisciplinary fields.Finally, the book discusses the role of artificial intelligence in enhancing healthcare applications and aims to engage the healthcare industry in adopting this innovative approach to improve patient care and outcomes.
    • RISC-V System-On-Chip Design

      • 1st Edition
      • January 1, 2025
      • David Harris + 3 more
      • English
      RISC-V Microprocessor System-On-Chip Design is written to be accessible to an advanced undergraduate audience with limited background. It explains concepts from operating systems, VLSI, and memory systems as necessary, and High school mathematics is sufficient preparation for most of the book, although the floating point and division chapters will be primarily of interest to those with a curiosity about computer arithmetic. Like Harris and Harris’s Digital Design and Computer Architecture textbooks, this book will appeal to students with easy-to-read and complete explanations, sidebars, and occasional humor and cartoons.It comes with an open-source implementation and will include end-of-chapter problems to extend the RISC-V processor in various ways. Ancillary materials include a GitHub repository with complete open-source SystemVerilog code, validation code in C and assembly language, and code for benchmarking and booting Linux.
    • Modeling, Dynamics and Control approaches for Modern Robotics

      • 1st Edition
      • November 3, 2025
      • Ahmad Taher Azar + 1 more
      • English
      • Paperback
        9 7 8 0 4 4 3 3 0 1 0 6 3
      • eBook
        9 7 8 0 4 4 3 3 0 1 0 7 0
      Modeling, Dynamics and Control approaches for Modern Robotics explores and investigates various theoretical and practical principles related to modeling, dynamics, and control in robotics. The objective is to enhance the understanding and development of robotic systems by applying these principles. Through accurate representations of robot kinematics and dynamics, researchers aim to effectively analyze and predict robot behavior. This title focuses on designing algorithms and control strategies for precise and efficient robotic system management.Additiona... the book delves into sensory feedback and perception systems for robots, advancements in autonomous vehicles, industrial automation, humanoid robots, and medical robotics, showcasing the integration of technology and computing power in modern applications. The study of control approaches and the development of optimized performance schemes are highlighted, demonstrating the significance of stability and adaptive response in changing environments. This comprehensive examination underscores the evolution and complexity of robotic systems, emphasizing their growing role in various sectors.
    • Minds, Machines, and Misinformation

      • 1st Edition
      • August 11, 2025
      • Don Donghee Shin
      • English
      • Paperback
        9 7 8 0 4 4 3 1 6 1 0 4 9
      • eBook
        9 7 8 0 4 4 3 1 6 1 0 5 6
      Algorithms have become the key organizer through which power is enacted in our society. A huge amount of data regarding our daily routines are monitored and analyzed to make recommendations that manage, control, and lead our behaviors in everyday life. AI, Humans, and Misinformation: How Does AI Alter Human Behavior and How Do Humans Influence Algorithmic Misinformation? is a guide to understanding the dynamics of AI and misinformation in human contexts by addressing meaningful questions—How does AI alter human behavior and how do humans influence algorithmic decision-making? In answering these questions, this book examines the role of misinformation, disinformation, and fake news, and shows readers how to develop AI methods and algorithms that combat misinformation by using AI design choices that provide users and developers alike with meaningful control over AI. This book brings together various perspectives on algorithms into an integrated conceptual framework, and provides a broad socio-technical analysis, addressing critical and ethical issues of misinformation and fake news. The book offers a compelling insight into the misinformation phenomenon and the future of AI-based society. Readers will find an integrated technical analysis of the logic and social implications of algorithmic processes. Reporting from the cutting edge of critical technical methods and research, the result is useful and constructive for developing the relations between algorithms and humans. This is an imperative methodology for understanding what is at stake as industry and government use AI to reshape the world.