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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

    • Optimum-Path Forest

      • 1st Edition
      • January 6, 2022
      • Alexandre Xavier Falcao + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 6 8 8 9
      • eBook
        9 7 8 0 1 2 8 2 2 6 8 9 6
      The Optimum-Path Forest (OPF) classifier was first published in 2008 in its supervised and unsupervised versions with applications in medicine and image classification. Since then, it has expanded to a variety of other applications such as remote sensing, electrical and petroleum engineering, and biology. In recent years, multi-label and semi-supervised versions were also developed to handle video classification problems. The book presents the principles, algorithms and applications of Optimum-Path Forest, giving the theory and state-of-the-art as well as insights into future directions.

    • Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering

      • 1st Edition
      • March 20, 2022
      • Goncalo Marques + 1 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 5 9 7 6
      • eBook
        9 7 8 0 3 2 3 8 5 5 9 8 3
      Current Trends and Advances in Computer-Aided Intelligent Environmental Data Engineering merges computer engineering and environmental engineering. The book presents the latest finding on how data science and AI-based tools are being applied in environmental engineering research. This application involves multiple domains such as data science and artificial intelligence to transform the data collected by intelligent sensors into relevant and reliable information to support decision-making. These tools include fuzzy logic, knowledge-based systems, particle swarm optimization, genetic algorithms, Monte Carlo simulation, artificial neural networks, support vector machine, boosted regression tree, simulated annealing, ant colony algorithm, decision tree, immune algorithm, and imperialist competitive algorithm. This book is a fundamental information source because it is the first book to present the foundational reference material in this new research field. Furthermore, it gives a critical overview of the latest cross-domain research findings and technological developments on the recent advances in computer-aided intelligent environmental data engineering.

    • Biomedical Image Synthesis and Simulation

      • 1st Edition
      • June 18, 2022
      • Ninon Burgos + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 3 4 9 7
      • eBook
        9 7 8 0 1 2 8 2 4 3 5 0 3
      Biomedical Image Synthesis and Simulation: Methods and Applications presents the basic concepts and applications in image-based simulation and synthesis used in medical and biomedical imaging. The first part of the book introduces and describes the simulation and synthesis methods that were developed and successfully used within the last twenty years, from parametric to deep generative models. The second part gives examples of successful applications of these methods. Both parts together form a book that gives the reader insight into the technical background of image synthesis and how it is used, in the particular disciplines of medical and biomedical imaging. The book ends with several perspectives on the best practices to adopt when validating image synthesis approaches, the crucial role that uncertainty quantification plays in medical image synthesis, and research directions that should be worth exploring in the future.

    • Computers as Components

      • 5th Edition
      • June 9, 2022
      • Marilyn Wolf
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 1 2 8 2
      • eBook
        9 7 8 0 3 2 3 8 5 1 2 9 9
      Computers as Components: Principles of Embedded Computing System Design, Fifth Edition continues to focus on foundational content in embedded systems technology and design while updating material throughout the book and introducing new content on machine learning and Internet-of-Things (IoT) systems.

    • Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data

      • 1st Edition
      • January 22, 2022
      • Akash Kumar Bhoi + 3 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 7 5 1 2
      • eBook
        9 7 8 0 3 2 3 9 0 3 4 8 6
      Cognitive and Soft Computing Techniques for the Analysis of Healthcare Data discusses the insight of data processing applications in various domains through soft computing techniques and enormous advancements in the field. The book focuses on the cross-disciplinary mechanisms and ground-breaking research ideas on novel techniques and data processing approaches in handling structured and unstructured healthcare data. It also gives insight into various information-processi... models and many memories associated with it while processing the information for forecasting future trends and decision making. This book is an excellent resource for researchers and professionals who work in the Healthcare Industry, Data Science, and Machine learning.

    • Role of Tumor Microenvironment in Breast Cancer and Targeted Therapies

      • 1st Edition
      • August 10, 2022
      • Manzoor Ahmad Mir
      • English
      • Paperback
        9 7 8 0 4 4 3 1 8 6 9 6 7
      • eBook
        9 7 8 0 4 4 3 1 8 6 9 7 4
      Role of Tumor Microenvironment in Breast Cancer and Targeted Therapies discusses the current understanding of breast cancer tumor microenvironment components, their role in tumorigenicity and the development of therapeutic resistance, along with updates on recent advances.

    • Artificial Intelligence for Healthcare Applications and Management

      • 1st Edition
      • January 13, 2022
      • Boris Galitsky + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 5 2 1 7
      • eBook
        9 7 8 0 1 2 8 2 4 5 2 2 4
      Artificial Intelligence for Healthcare Applications and Management introduces application domains of various AI algorithms across healthcare management. Instead of discussing AI first and then exploring its applications in healthcare afterward, the authors attack the problems in context directly, in order to accelerate the path of an interested reader toward building industrial-strength healthcare applications. Readers will be introduced to a wide spectrum of AI applications supporting all stages of patient flow in a healthcare facility. The authors explain how AI supports patients throughout a healthcare facility, including diagnosis and treatment recommendations needed to get patients from the point of admission to the point of discharge while maintaining quality, patient safety, and patient/provider satisfaction. AI methods are expected to decrease the burden on physicians, improve the quality of patient care, and decrease overall treatment costs. Current conditions affected by COVID-19 pose new challenges for healthcare management and learning how to apply AI will be important for a broad spectrum of students and mature professionals working in medical informatics. This book focuses on predictive analytics, health text processing, data aggregation, management of patients, and other fields which have all turned out to be bottlenecks for the efficient management of coronavirus patients.

    • The Designer's Guide to the Cortex-M Processor Family

      • 3rd Edition
      • December 2, 2022
      • Trevor Martin
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 4 9 4 8
      • eBook
        9 7 8 0 3 2 3 8 5 4 9 5 5
      The Designer’s Guide to the Cortex-M Microcontrollers, Third Edition provides an easy-to-understand introduction to the concepts required to develop programs in C with a Cortex-M based microcontroller. Sections cover architectural descriptions that are supported with practical examples, enabling readers to easily develop basic C programs to run on the Cortex-M0/M0+/M3 and M4 and M7 and examine advanced features of the Cortex architecture, such as memory protection, operating modes and dual stack operation. Final sections examine techniques for software testing and code reuse specific to Cortex-M microcontrollers. Users will learn the key differences between the Cortex-M0/M0+/M3 and M4 and M7; how to write C programs to run on Cortex-M based processors; how to make the best use of the CoreSight debug system; the Cortex-M operating modes and memory protection; advanced software techniques that can be used on Cortex-M microcontrollers, and much more.

    • Deep Learning for Sustainable Agriculture

      • 1st Edition
      • January 9, 2022
      • Ramesh Chandra Poonia + 2 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 2 1 4 2
      • eBook
        9 7 8 0 3 2 3 9 0 3 6 2 2
      The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm.

    • Digital Twin for Healthcare

      • 1st Edition
      • November 21, 2022
      • Abdulmotaleb El Saddik
      • English
      • Paperback
        9 7 8 0 3 2 3 9 9 1 6 3 6
      • eBook
        9 7 8 0 3 2 3 9 5 0 9 5 4
      Digital Twins for Healthcare: Design, Challenges and Solutions establishes the state-of-art in the specification, design, creation, deployment and exploitation of digital twins' technologies for healthcare and wellbeing. A digital twin is a digital replication of a living or non-living physical entity. When data is transmitted seamlessly, it bridges the physical and virtual worlds, thus allowing the virtual entity to exist simultaneously with the physical entity. A digital twin facilitates the means to understand, monitor, and optimize the functions of the physical entity and provide continuous feedback. It can be used to improve citizens' quality of life and wellbeing in smart cities and the virtualization of industrial processes.

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