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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.

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21-30 of 5367 results in All results

Deep Learning for COVID Image Analysis

  • 1st Edition
  • January 1, 2029
  • Hayit Greenspan + 1 more
  • English
Deep Learning for COVID Image Analysis provides a comprehensive overview of the most recently developed deep learning-based systems and solutions for COVID-19 image analysis, assembling a collection of state-of-the-art works for detection, severity analysis and predictive analysis, all of which are tools that support handling of the disease. The extraordinarily rapid spread of this pandemic has demonstrated that a new disease entity with a subset of relatively unique characteristics can pose a major new clinical challenge that requires new diagnostic tools in imaging.The AI/Deep Learning Imaging community has shown in many recent publications that rapidly developed AI-based automated CT and Xray image analysis tools can achieve high accuracy in the detection of Coronavirus positive patients as well as quantifying the disease burden.

Artificial Intelligence Strategies for Brain Tumor Diagnosis

  • 1st Edition
  • January 1, 2029
  • Ayman S. El-Baz + 1 more
  • English
Artificial Intelligence Strategies for Brain Tumor Diagnosis: Postoperative Analysis presents the latest advances in Artificial Intelligence applied to clinical diagnosis and treatment of Brain Tumors. Advances in the role of segmentation, classification, and postoperative analysis are covered, including relevant case studies. For patients with a brain tumor, the first step in treatment is often surgery to remove as much of the mass as possible. A tumor sample obtained and analyzed during surgery can help to precisely diagnose the tumor and define the margins between tumor and healthy brain tissue. In this book, the authors present an overview of different Artificial Intelligent techniques used in the brain care domain including classification, segmentation, organizational preparation, postoperative analysis, and predictive methods. Furthermore, the authors provide a thorough description of recent classification methods based on brain connectivity. Taking into account recent developments and the rapidly growing potential of the field, the authors discuss how AI might transform brain care in the near and long term, identifying open issues and promising directions for future work. Artificial Intelligence Strategies for Brain Tumor Diagnosis: Postoperative Analysis includes three Parts: Brain Tumor Segmentation, Brain Tumor Classification, and Postoperative Analysis of Brain Tumors.

Research Methods in Human-Computer Interaction

  • 3rd Edition
  • September 1, 2027
  • English
Research Methods in Human-Computer Interaction is a comprehensive guide to performing research and is essential reading for both quantitative and qualitative methods. Since the first edition was published in 2009, the book has been adopted for use at leading universities around the world, including Harvard University, Carnegie-Mellon University, the University of Washington, the University of Toronto, HiOA (Norway), KTH (Sweden), Tel Aviv University (Israel), and many others. Chapters cover a broad range of topics relevant to the collection and analysis of HCI data, going beyond experimental design and surveys, to cover ethnography, diaries, physiological measurements, case studies, crowdsourcing, and other essential elements in the well-informed HCI researcher's toolkit. Continual technological evolution has led to a need for this updated third edition, to reflect the most recent research in the field and newer trends in research methodology. This Research Methods in HCI revision contains updates throughout, including a reorganization of chapters based on the steps that researchers take in planning and executing research projects, and several new chapters covering everything from remote research, to HCI and AI, to how your research can have an impact.

Encyclopedia of Artificial Intelligence

  • 1st Edition
  • May 3, 2027
  • Maki Habib
  • English
The Encyclopedia of AI: Foundations, Innovations, and Future Directions is a comprehensive compendium investigating and exploring the multifaceted field of Artificial Intelligence (AI). Designed to serve as a foundational resource, this Encyclopedia covers various topics, from fundamental concepts to cutting-edge advancements and future trajectories in AI research advancements and applications. With concise and accessible entries, this Encyclopedia caters to a diverse audience, including undergraduate and graduate students advancing or embarking on their AI journey, professionals seeking to deepen their understanding of AI technologies and theories, and educators and researchers needing a reliable reference guide. Each contribution gives readers essential knowledge, contextual backgrounds, and practical insights into various AI-related domains. The Encyclopedia offers a holistic view of AI technologies and their real-world applications, from machine learning algorithms and AI architectures to natural language processing, computer vision, and robotics. Moreover, the Encyclopedia goes beyond traditional approaches by emphasizing recent innovations and prospects in AI. It incorporates practical case studies to demonstrate the real-world relevance of theoretical concepts, fostering a deeper understanding of AI's impact across industries. As AI evolves rapidly, this encyclopedia is a timely and indispensable resource. Clarifying complex AI concepts and exploring emerging trends equips readers with the knowledge and inspiration to engage with AI technologies across diverse domains. Whether used as a learning tool, a reference guide, or a source of inspiration, "The Encyclopedia of AI" is poised to become an essential companion for anyone interested in unlocking the potential of artificial intelligence in today's rapidly changing world.

Theory and Methods of Piecewise Defined Fractional Operators

  • 1st Edition
  • December 1, 2026
  • Abdon Atangana + 1 more
  • English
Theory and Methods of Piecewise Defined Fractional Operators introduces new mathematical methods to derive complex modeling solutions with stability, consistency, and convergence. These tools include new types of non-local derivatives and integrals, such as fractal-fractional derivatives and integrals. Drs. Atangana and Araz present the theoretical and numerical analyses of the newly introduced piecewise differential and integral operators where crossover behaviors are observed, as well as their applications to real-world problems. The book contains foundational concepts that will help readers better understand piecewise differential and integral calculus and their applications to modeling processes with crossover behaviors. Several Cauchy problems with piecewise differential operators are considered, and their existence and uniqueness under some conditions are presented; in particular, the Carathéodory principle is used to ensure the existence and uniqueness of these new Cauchy problems. New numerical schemes are introduced to derive numerical solutions to these new equations, and the stability, consistency, and convergence analysis of these new numerical approaches are also presented.

Epidemiological Modeling with Application to Covid-19

  • 1st Edition
  • December 1, 2026
  • Abdon Atangana + 1 more
  • English
Epidemiological Modeling with Application to Covid-19 presents information about statistical, numerical, stability, and theoretical analyses for nine different Covid-19 models. Those models are considered with classical and fractional derivatives, which is a generalization of the classical analysis. The authors present their newly introduced rate indicator function for the prediction of the waves of Covid-19 spread. Moreover, future prediction of Covid-19 spread is presented for some countries. The authors also provide a new approach to modeling epidemiological issues in general, which has been tested against the spread of COVID-19 in several nations.This book provides in-depth analysis of the spread of Covid-19, including discussion of theoretical and numerical results, including a novel modeling method called strength numbers that was created under the umbrella of acceleration, which provides a determiner of the power of disease spread. These significant characteristics might be the key to understanding and anticipating the spread of infections and diseases more generally.

Medical Data Processing

  • 1st Edition
  • August 1, 2026
  • Dalila Cherifi
  • English
"Medical Data Processing" discusses the collection, manipulation, and analysis of data related to healthcare and medical information. This book presents a systematic approach employing diverse technologies and methods to adeptly manage, organize, and extract meaningful insights from the substantial volumes of data generated within the healthcare system. It is a resource contributing to the enhancement of patient care by leveraging data-driven insights, streamlining healthcare operations through efficient data management strategies, and fostering advancements in medical research through the informed analysis of complex datasets. The book is an indispensable tool at the intersection of technology and healthcare, playing a transformative role in the optimization of patient outcomes, healthcare workflows, and the progression of medical knowledge.

Artificial Intelligence Applications in Emerging Healthcare Technologies

  • 1st Edition
  • July 1, 2026
  • Miguel Antonio Wister Ovando + 2 more
  • English
"Artificial Intelligence Applications in Emerging Healthcare Technologies" presents the latest advances and state-of-the-art methods and applications of computer science and emerging AI technologies in health and medicine. It explores the impact of artificial intelligence (AI) in healthcare for medical decision-making and data analysis, tackling topics such as cloud computing, cybersecurity, the internet of things, natural language processing, virtual health, data science applied to healthcare, personalized medicine, imaging, diagnosis, drug discovery, and diseases, among others. It is a great resource for researchers and students to learn how machine learning algorithms and other data science techniques have been implemented to solve healthcare-related problems. Chapters present adaptations or improvements on previous models and algorithms to process data from different sources. Other chapters investigate new formulations for the optimization of known procedures and algorithms. Finally, all chapters use experimental methods to study problems of interest in healthcare.

Cybersecurity Defensive Walls in Edge Computing

  • 1st Edition
  • June 1, 2026
  • Fatos Xhafa + 3 more
  • English
Cybersecurity Defensive Walls in Edge Computing dives into the creation of robust cybersecurity defenses for increasingly vulnerable edge devices. This book examines the unique security challenges of edge environments, including limited resources and potentially untrusted networks, providing fundamental concepts for real-time vulnerability detection and mitigation through novel system architectures, experimental frameworks, and AI/ML techniques. Researchers and industry professionals working in cybersecurity, edge computing, cloud computing, defensive technologies, and threat intelligence will find this to be a valuable resource that illuminates critical aspects of edge-based security to advance theoretical analysis, system design, and practical implementation of defensive walls. With a focus on fast-growing edge application scenarios, this book offers valuable insights into strengthening real-time security for the proliferation of interconnected edge devices.