Skip to main content
Elsevier
View Cart
My account

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

    • The Natural Language for Artificial Intelligence

      • 1st Edition
      • March 28, 2021
      • Dioneia Motta Monte-Serrat + 1 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 1 1 8 9
      • eBook
        9 7 8 0 3 2 3 8 5 9 2 1 9
      The Natural Language for Artificial Intelligence presents the biological and logical structure typical of human language in its dynamic mediating process between reality and the human mind. The book explains linguistic functioning in the dynamic process of human cognition when forming meaning. After that, an approach to artificial intelligence (AI) is outlined, which works with a more restricted concept of natural language that leads to flaws and ambiguities. Subsequently, the characteristics of natural language and patterns of how it behaves in different branches of science are revealed to indicate ways to improve the development of AI in specific fields of science. A brief description of the universal structure of language is also presented as an algorithmic model to be followed in the development of AI. Since AI aims to imitate the process of the human mind, the book shows how the cross-fertilization between natural language and AI should be done using the logical-axiomatic structure of natural language adjusted to the logical-mathematical processes of the machine.

    • Cognitive Computing for Human-Robot Interaction

      • 1st Edition
      • August 13, 2021
      • Mamta Mittal + 2 more
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 7 6 9 7
      • eBook
        9 7 8 0 3 2 3 8 5 6 4 7 8
      Cognitive Computing for Human-Robot Interaction: Principles and Practices explores the efforts that should ultimately enable society to take advantage of the often-heralded potential of robots to provide economical and sustainable computing applications. This book discusses each of these applications, presents working implementations, and combines coherent and original deliberative architecture for human–robot interactions (HRI). Supported by experimental results, it shows how explicit knowledge management promises to be instrumental in building richer and more natural HRI, by pushing for pervasive, human-level semantics within the robot's deliberative system for sustainable computing applications. This book will be of special interest to academics, postgraduate students, and researchers working in the area of artificial intelligence and machine learning. Key features: Introduces several new contributions to the representation and management of humans in autonomous robotic systems; Explores the potential of cognitive computing, robots, and HRI to generate a deeper understanding and to provide a better contribution from robots to society; Engages with the potential repercussions of cognitive computing and HRI in the real world.

    • Deep Learning for Chest Radiographs

      • 1st Edition
      • July 16, 2021
      • Yashvi Chandola + 3 more
      • English
      • Paperback
        9 7 8 0 3 2 3 9 0 1 8 4 0
      • eBook
        9 7 8 0 3 2 3 9 0 6 8 6 9
      Deep Learning for Chest Radiographs enumerates different strategies implemented by the authors for designing an efficient convolution neural network-based computer-aided classification (CAC) system for binary classification of chest radiographs into "Normal" and "Pneumonia." Pneumonia is an infectious disease mostly caused by a bacteria or a virus. The prime targets of this infectious disease are children below the age of 5 and adults above the age of 65, mostly due to their poor immunity and lower rates of recovery. Globally, pneumonia has prevalent footprints and kills more children as compared to any other immunity-based disease, causing up to 15% of child deaths per year, especially in developing countries. Out of all the available imaging modalities, such as computed tomography, radiography or X-ray, magnetic resonance imaging, ultrasound, and so on, chest radiographs are most widely used for differential diagnosis between Normal and Pneumonia. In the CAC system designs implemented in this book, a total of 200 chest radiograph images consisting of 100 Normal images and 100 Pneumonia images have been used. These chest radiographs are augmented using geometric transformations, such as rotation, translation, and flipping, to increase the size of the dataset for efficient training of the Convolutional Neural Networks (CNNs). A total of 12 experiments were conducted for the binary classification of chest radiographs into Normal and Pneumonia. It also includes in-depth implementation strategies of exhaustive experimentation carried out using transfer learning-based approaches with decision fusion, deep feature extraction, feature selection, feature dimensionality reduction, and machine learning-based classifiers for implementation of end-to-end CNN-based CAC system designs, lightweight CNN-based CAC system designs, and hybrid CAC system designs for chest radiographs. This book is a valuable resource for academicians, researchers, clinicians, postgraduate and graduate students in medical imaging, CAC, computer-aided diagnosis, computer science and engineering, electrical and electronics engineering, biomedical engineering, bioinformatics, bioengineering, and professionals from the IT industry.

    • Intelligence Science

      • 1st Edition
      • April 16, 2021
      • Zhongzhi Shi
      • English
      • Paperback
        9 7 8 0 3 2 3 8 5 3 8 0 4
      • eBook
        9 7 8 0 3 2 3 8 8 4 9 8 3
      Intelligence Science: Leading the Age of Intelligence covers the emerging scientific research on the theory and technology of intelligence, bringing together disciplines such as neuroscience, cognitive science, and artificial intelligence to study the nature of intelligence, the functional simulation of intelligent behavior, and the development of new intelligent technologies. The book presents this complex, interdisciplinary area of study in an accessible volume, introducing foundational concepts and methods, and presenting the latest trends and developments. Chapters cover the Foundations of neurophysiology, Neural computing, Mind models, Perceptual intelligence, Language cognition, Learning, Memory, Thought, Intellectual development and cognitive structure, Emotion and affect, and more. This volume synthesizes a very rich and complex area of research, with an aim of stimulating new lines of enquiry.

    • 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.

    • Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering

      • 1st Edition
      • March 25, 2021
      • Ilker Ozsahin + 2 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 4 0 8 6 1
      • eBook
        9 7 8 0 1 2 8 2 4 0 8 7 8
      Applications of Multi-Criteria Decision-Making Theories in Healthcare and Biomedical Engineering contains several practical applications on how decision-making theory could be used in solving problems relating to the selection of best alternatives. The book focuses on assisting decision-makers (government, organizations, companies, general public, etc.) in making the best and most appropriate decision when confronted with multiple alternatives. The purpose of the analytical MCDM techniques is to support decision makers under uncertainty and conflicting criteria while making logical decisions. The knowledge of the alternatives of the real-life problems, properties of their parameters, and the priority given to the parameters have a great effect on consequences in decision-making. In this book, the application of MCDM has been provided for the real-life problems in health and biomedical engineering issues.

    • Mobile Edge Artificial Intelligence

      • 1st Edition
      • August 7, 2021
      • Yuanming Shi + 3 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 8 1 7 2
      • eBook
        9 7 8 0 1 2 8 2 3 8 3 5 6
      Mobile Edge Artificial Intelligence: Opportunities and Challenges presents recent advances in wireless technologies and nonconvex optimization techniques for designing efficient edge AI systems. The book includes comprehensive coverage on modeling, algorithm design and theoretical analysis. Through typical examples, the powerfulness of this set of systems and algorithms is demonstrated, along with their abilities to make low-latency, reliable and private intelligent decisions at network edge. With the availability of massive datasets, high performance computing platforms, sophisticated algorithms and software toolkits, AI has achieved remarkable success in many application domains. As such, intelligent wireless networks will be designed to leverage advanced wireless communications and mobile computing technologies to support AI-enabled applications at various edge mobile devices with limited communication, computation, hardware and energy resources.

    • Visual Thinking for Information Design

      • 2nd Edition
      • March 26, 2021
      • Colin Ware
      • English
      • Paperback
        9 7 8 0 1 2 8 2 3 5 6 7 6
      • eBook
        9 7 8 0 1 2 8 2 3 5 6 8 3
      Visual Thinking for Information Design, Second Edition brings the science of perception to the art of design. The book takes what we now know about perception, cognition and attention and transforms it into concrete advice that students and designers can directly apply. It demonstrates how designs can be considered as tools for cognition and extensions of the viewer’s brain in much the same way that a hammer is an extension of the user’s hand. The book includes hundreds of examples, many in the form of integrated text and full-color diagrams. Renamed from the first edition, Visual Thinking for Design, to more accurately reflect its focus on infographics, this timely revision has been updated throughout and includes more content on pattern perception, the addition of new material illustrating color assimilation, and a new chapter devoted to communicating ideas through images.

    • Recent Trends in Computational Intelligence Enabled Research

      • 1st Edition
      • July 31, 2021
      • Siddhartha Bhattacharyya + 4 more
      • English
      • Paperback
        9 7 8 0 1 2 8 2 2 8 4 4 9
      • eBook
        9 7 8 0 3 2 3 8 5 1 7 9 4
      The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing.

    • Thinking Machines

      • 1st Edition
      • March 27, 2021
      • Shigeyuki Takano
      • English
      • Paperback
        9 7 8 0 1 2 8 1 8 2 7 9 6
      • eBook
        9 7 8 0 1 2 8 1 8 2 8 0 2
      Thinking Machines: Machine Learning and Its Hardware Implementation covers the theory and application of machine learning, neuromorphic computing and neural networks. This is the first book that focuses on machine learning accelerators and hardware development for machine learning. It presents not only a summary of the latest trends and examples of machine learning hardware and basic knowledge of machine learning in general, but also the main issues involved in its implementation. Readers will learn what is required for the design of machine learning hardware for neuromorphic computing and/or neural networks.This is a recommended book for those who have basic knowledge of machine learning or those who want to learn more about the current trends of machine learning.

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