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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

    • Advanced Data Mining Tools and Methods for Social Computing

      • 1st Edition
      • January 14, 2022
      • Sourav De + 3 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 7 0 8 6
      • eBook
        9 7 8 0 3 2 3 8 5 7 0 9 3
      Advanced Data Mining Tools and Methods for Social Computing explores advances in the latest data mining tools, methods, algorithms and the architectures being developed specifically for social computing and social network analysis. The book reviews major emerging trends in technology that are supporting current advancements in social networks, including data mining techniques and tools. It also aims to highlight the advancement of conventional approaches in the field of social networking. Chapter coverage includes reviews of novel techniques and state-of-the-art advances in the area of data mining, machine learning, soft computing techniques, and their applications in the field of social network analysis.

    • 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.

    • 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.

    • Anomaly Detection and Complex Event Processing Over IoT Data Streams

      • 1st Edition
      • January 7, 2022
      • Patrick Schneider + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 8 1 8 9
      • eBook
        9 7 8 0 1 2 8 2 3 8 1 9 6
      Anomaly Detection and Complex Event Processing over IoT Data Streams: With Application to eHealth and Patient Data Monitoring presents advanced processing techniques for IoT data streams and the anomaly detection algorithms over them. The book brings new advances and generalized techniques for processing IoT data streams, semantic data enrichment with contextual information at Edge, Fog and Cloud as well as complex event processing in IoT applications. The book comprises fundamental models, concepts and algorithms, architectures and technological solutions as well as their application to eHealth. Case studies, such as the bio-metric signals stream processing are presented –the massive amount of raw ECG signals from the sensors are processed dynamically across the data pipeline and classified with modern machine learning approaches including the Hierarchical Temporal Memory and Deep Learning algorithms. The book discusses adaptive solutions to IoT stream processing that can be extended to different use cases from different fields of eHealth, to enable a complex analysis of patient data in a historical, predictive and even prescriptive application scenarios. The book ends with a discussion on ethics, emerging research trends, issues and challenges of IoT data stream processing.

    • 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.

    • Cybersecurity for Connected Medical Devices

      • 1st Edition
      • November 9, 2021
      • Arnab Ray
      • English
      • Paperback
        9 7 8 0 1 2 8 1 8 2 6 2 8
      • eBook
        9 7 8 0 1 2 8 1 8 2 6 3 5
      The cybersecurity of connected medical devices is one of the biggest challenges facing healthcare today. The compromise of a medical device can result in severe consequences for both patient health and patient data.　Cybersecurity for Connected Medical Devices covers all aspects of medical device cybersecurity, with a focus on cybersecurity capability development and maintenance, system and software threat modeling, secure design of medical devices, vulnerability management, and integrating cybersecurity design aspects into a medical device manufacturer's Quality Management Systems (QMS). This book is geared towards engineers interested in the medical device cybersecurity space, regulatory, quality, and human resources specialists, and organizational leaders interested in building a medical device cybersecurity program.　

    • Advanced Methods and Deep Learning in Computer Vision

      • 1st Edition
      • November 9, 2021
      • E. R. Davies + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 1 0 9 9
      • eBook
        9 7 8 0 1 2 8 2 2 1 4 9 5
      Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students.

    • Cognitive Big Data Intelligence with a Metaheuristic Approach

      • 1st Edition
      • November 9, 2021
      • Sushruta Mishra + 4 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 1 1 7 6
      • eBook
        9 7 8 0 3 2 3 8 5 1 1 8 3
      Cognitive Big Data Intelligence with a Metaheuristic Approach presents an exact and compact organization of content relating to the latest metaheuristics methodologies based on new challenging big data application domains and cognitive computing. The combined model of cognitive big data intelligence with metaheuristics methods can be used to analyze emerging patterns, spot business opportunities, and take care of critical process-centric issues in real-time. Various real-time case studies and implemented works are discussed in this book for better understanding and additional clarity. This book presents an essential platform for the use of cognitive technology in the field of Data Science. It covers metaheuristic methodologies that can be successful in a wide variety of problem settings in big data frameworks.

    • Cyber-Physical Systems

      • 1st Edition
      • October 30, 2021
      • Ramesh Chandra Poonia + 5 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 5 5 7 6
      • eBook
        9 7 8 0 3 2 3 8 5 3 5 7 6
      Cyber-Physical Systems: AI and COVID-19 highlights original research which addresses current data challenges in terms of the development of mathematical models, cyber-physical systems-based tools and techniques, and the design and development of algorithmic solutions, etc. It reviews the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS) and reviews tools and techniques that can be used. This book will act as a resource to guide COVID researchers as they move forward with clinical and epidemiological studies on this outbreak, including the technical concepts of gathering, processing and analyzing data from cyber-physical systems (CPS). The major problem in the identification of COVID-19 is detection and diagnosis due to non-availability of medicine. In this situation, only one method, Reverse Transcription Polymerase Chain Reaction (RT-PCR) has been widely adopted and used for diagnosis. With the evolution of COVID-19, the global research community has implemented many machine learning and deep learning-based approaches with incremental datasets. However, finding more accurate identification and prediction methods are crucial at this juncture.

    • Handbook of Pediatric Brain Imaging

      • 1st Edition
      • Volume 2
      • October 27, 2021
      • Hao Huang + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 1 6 6 3 3 8
      • eBook
        9 7 8 0 1 2 8 1 6 6 4 2 0
      Handbook of Pediatric Brain Imaging: Methods and Applications presents state-of-the-art research on pediatric brain image acquisition and analysis from a broad range of imaging modalities, including MRI, EEG and MEG. With rapidly developing methods and applications of MRI, this book strongly emphasizes pediatric brain MRI, elaborating on the sub-categories of structure MRI, diffusion MRI, functional MRI, perfusion MRI and other MRI methods. It integrates a pediatric brain imaging perspective into imaging acquisition and analysis methods, covering head motion, small brain sizes, small cerebral blood flow of neonates, dynamic cortical gyrification, white matter tract growth, and much more.

Related subjects

Applications

Artificial intelligence

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Computer systems organization

Computer vision and pattern recognition

Computing milieux

Data

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Hardware and architecture

Information systems

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Software

Theory and mathematics