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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.

BooksJournals

    • Robotics for Intervention in Healthcare

      From Technology to Clinical Practice
      • 1st Edition
      • Françoise J Siepel
      • English
      Robotics for Intervention in Healthcare: From Technology to Clinical Practice bridges the gap between deep-core robotic intervention technology and clinical aspects, including content that is appropriate for physicians and clinicians. The book gives insights on the importance of connectivity in early stages, thoroughly addressing which aspects are important to improve the innovation chain.

    • Digital Supply Chain Transformation

      Implementing Technology, Analytics, and Data-Driven Solutions
      • 1st Edition
      • Vinaytosh Mishra
      • English
      Digital Supply Chain Transformation: Implementing Technology, Analytics, and Data-Driven Solutions offers an in-depth exploration of how digital innovation is reshaping modern supply chain management. The book seamlessly blends theoretical concepts with practical application, ensuring readers not only grasp fundamental supply chain principles but also see how technologies like machine learning, AI, and system dynamics modeling are transforming the industry. Readers are guided through the evolving landscape of supply chains, learning to harness digital tools and analytics for improved efficiency, accuracy, and end-to-end visibility in operations.This comprehensive resource equips readers to tackle real-world challenges by applying advanced technologies and analytics to supply chain problems. It highlights the growing importance of data-driven decision-making, encourages critical evaluation of strategies and solutions, and anticipates emerging trends and future opportunities. By merging theory with hands-on practice, the book enables professionals to drive innovation and recommend informed improvements in the rapidly advancing field of supply chain management.

    • Digital Transformation and Equitable Global Health

      A Future-Ready Perspective
      • 1st Edition
      • Arletty Pinel + 2 more
      • English
      Digital Transformation and Equitable Global Health: A Future-Ready Perspective presents a collective body of knowledge and global experiences that demonstrate current status and future trends in the use of exponential technologies and their potential for poverty reduction, improving health outcomes, strengthening health systems, and transforming traditional development aid structures. The book uses a translational innovation perspective to guide the reader—regardless of their area of expertise—on the rationale behind the co-creation of human-centered, affordable, and sustainable digital solutions.It addresses the interest of professionals from multiple areas (e.g., technology, health, social development, global financing), and it is a valuable resource for professionals, social scientists, practitioners, researchers, instructors, and undergraduate and graduate students interested in understanding the challenges and complexities of global public health and the applied uses of health technologies for equitable access to primary health care and universal health coverage.

    • Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence

      • 1st Edition
      • Manuel González Canché
      • English
      Data Science and Interactive Visualization Tools for the Analysis of Qualitative Evidence empowers qualitative and mixed methods researchers in the data science movement by offering no-code, cost-free software access so that they can apply cutting-edge and innovative methods to synthetize qualitative data. The book builds on the idea that qualitative and mixed methods researchers should not have to learn to code to benefit from rigorous open-source, cost-free software that uses artificial intelligence, machine learning, and data visualization tools—just as people do not need to know C++ or TypeScript to benefit from Microsoft Word. The real barrier is the hundreds of R code lines required to apply these concepts to their databases. By removing the coding proficiency hurdle, this book will empower their research endeavors and help them become active members of and contributors to the applied data science community. The book offers a comprehensive explanation of data science and machine learning methodologies, along with access to software application tools to implement these techniques without any coding proficiency. The book addresses the need for innovative tools that enable researchers to tap into the insights that come out of cutting-edge data science tools with absolutely no computer language literacy requirements.

    • Federated Learning for the Metaverse

      Applications in Virtual Environments
      • 1st Edition
      • Noor Zaman Jhanjhi + 3 more
      • English
      Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.

    • Metaverse and AI in Healthcare

      A Federated Learning Approach
      • 1st Edition
      • Jyotir Moy Chatterjee + 1 more
      • English
      Metaverse and AI in Healthcare: A Federated Learning Approach addresses the transformative integration of artificial intelligence and metaverse technologies in healthcare. It fills a critical gap by exploring how federated learning enables secure, decentralized data sharing and personalized medicine in virtual health platforms, meeting urgent demands for privacy, interoperability, and innovation. The book is structured into four parts covering foundational AI and federated learning concepts, augmented reality and metaverse applications, legal and cybersecurity challenges, and emerging strategic trends. Contributors from academia and industry present chapters on predictive modeling, cybersecurity frameworks, AR fitness, legal perspectives, and AI-driven medical tourism, supported by case studies and technical explanations. This reference equips graduate students, researchers, and professionals in academia and industry who specialize in computer science, federated learning, biomedical engineering, and digital healthcare with practical knowledge and forward-looking analysis. It empowers readers to navigate evolving digital health ecosystems, addressing data privacy, customized care, and global access challenges through federated learning and metaverse solutions.

    • Essential Kubeflow

      Engineering ML Workflows on Kubernetes
      • 1st Edition
      • Prashanth Josyula + 2 more
      • English
      Essential Kubeflow: Engineering ML Workflows on Kubernetes provides the tools needed to transform ML workflows from experimental notebooks to production-ready platforms. Through hands-on examples and production-tested patterns, readers will master essential skills for building enterprise-grade Machine Learning platforms, including architecting production systems on Kubernetes, designing end-to-end ML pipelines, implementing robust model serving, efficiently scaling workloads, managing multi-user environments, deploying automated MLOps workflows, and integrating with existing ML tools. Whether you're a Machine Learning engineer looking to operationalize models, a platform engineer diving into ML infrastructure, or a technical leader architecting ML systems, this book provides solutions for real-world challenges.With this comprehensive guide to Kubeflow, a widely adopted open source MLOps platforms for automating ML workloads, readers will have the expertise to build and maintain scalable ML platforms that can handle the demands of modern enterprise AI initiatives.

    • Pioneering Autonomous Technology: A Deep Dive into Hyper Automation

      • 1st Edition
      • Volume 143
      • English
      Pioneering Autonomous Technology: A Deep Dive into Hyper Automation, Volume 143 in the Advances in Computers series, showcases the transformative role of artificial intelligence, deep learning, and machine learning in creating safer, more efficient, and socially inclusive environments. This volume explores how autonomous technologies are reshaping healthcare, transportation, agriculture, and urban living. Chapters cover important topics such as a Survey on Deep Learning Based Autonomous Medical Diagnosis Models for Chronic Disease Identification, Human-Robot Interaction: Ensuring Safe and Effective Coordination, Blazing Trails: Cutting-Edge Technologies Revolutionizing Forest Fire Screening, Connected Communities: Fostering Social Inclusion and Equity in Smart Cities through IoT Integration, and much more.Additional chapters cover a Preliminary Study of Retinal Biomarkers Detection on Fundus Images for the Diagnosis of Alzheimer’s and Parkinson’s Diseases, Deep Learning Driven Classification of Sweet Lime Leaves: A Superior CNN Approach for Agricultural Automation, Machine Learning in Healthcare: Advancements, Applications, and Challenges, Feature Extraction and Object Recognition in Autonomous Systems, The Future of Autonomous Vehicles: Industry Trends, Technologies, and Challenges, Autonomous Systems: Shaping the Future of Industries and Transportation, and many other topics that will be of interest to readers.

    • Deep Learning Applications in Neuroinformatics

      Advances, Methods, and Perspectives
      • 1st Edition
      • Karthik Ramamurthy
      • English
      Deep Learning Applications in Neuroinformatics: Advances, Methods, and Perspectives explores how deep learning revolutionizes neuroinformatics, covering the latest methods and applications of deep learning in analyzing neuroimaging data from EEG, MRI, PET, and more. The book addresses critical neurological disorders like Alzheimer’s disease, Mild Cognitive Impairment, Stroke, and Autism Spectrum Disorder, bridging the gap between neuroscience and artificial intelligence. It is an ideal resource for researchers, practitioners, and students with insights from leading experts.

    • Distributed AI in the Modern World

      Technical and Social Aspects of Interacting Intelligent Agents
      • 1st Edition
      • Andrei Olaru + 3 more
      • English
      Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level.

Related subjects

Applications

Artificial intelligence

Business intelligence

Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

Graphics cad hci

Hardware and architecture

Information systems

Internet and web technology

Software

Theory and mathematics