Books in Artificial intelligence general

21-30 of 102 results in All results

Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment

• 1st Edition
• April 4, 2024
• Zhijun Chen
• English
• Paperback 978-0-443-27316-2

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• eBook 978-0-443-27317-9

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Construction Methods for an Autonomous Driving Map in an Intelligent Network Environment not only supports the development of Intelligent & Connected Transportation, but also promotes the landing application of autonomous driving. Areas covered include the fusion target perception method based on vehicle vision and millimeter wave radar, cross-field of view object perception method, vehicle motion recognition method based on vehicle road fusion information, vehicle trajectory prediction method based on improved hybrid neural network and driving map construction driven by road perception fusion are introduced in this book.Benefiting from the development of computer technique, the advanced machine learning and artificial intelligence theories are used by this book to show readers the construction process of the Autonomous Driving Map.

Ethics in Online AI-Based Systems

• 1st Edition
• April 1, 2024
• Santi Caballé + 2 more
• English
• Paperback 978-0-443-18851-0

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• eBook 978-0-443-18850-3

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Ethics in Online AI-Based Systems: Risks and Opportunities in Current Technological Trends creates a space to explore the ethical relevance that new technologies under development may have. Stimulating reflection and considerations with respect to the design, deployment, and use of technology helps readers guide current and future technological advancements from an ethically informed position to ensure that such advancements contribute towards solving current global and social challenges that we, as a society, have today. This will not only be useful for researchers and professional engineers, but also for educators, policy makers, and ethicists.Recent technological advancements have deeply transformed society and the way people interact with each other. Instantaneous communication platforms have allowed connections with other people, forming global communities and creating unprecedented opportunities in many sectors, making access to online resources more ubiquitous by reducing limitations imposed by geographical distance and temporal constrains. These technological developments bear ethically relevant consequences with their deployment, and legislations often lag behind such advancements. Because the appearance and deployment of these technologies happen much faster than legislative procedures, the way these technologies affect social interactions have profound ethical effects before any legislative regulation can be built in order to prevent and mitigate those effects.

Computational Intelligence and Blockchain in Complex Systems

• 1st Edition
• March 26, 2024
• Fadi Al-Turjman
• English
• Paperback 978-0-443-13268-1

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• eBook 978-0-443-13274-2

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Computational Intelligence and Blockchain in Complex Systems: System Security and Interdisciplinary Applications provides readers with a guide to understanding the dynamics of AI, machine learning, and computational intelligence in blockchain, and how these rapidly developing technologies are revolutionizing a variety of interdisciplinary research fields and applications. This book examines the role of computational intelligence and machine learning in the development of algorithms to deploy blockchain technology across a number of applications, including healthcare, insurance, smart grid, smart contracts, digital currency, precision agriculture, and supply chain. The authors cover the unique and developing intersection between cyber security and blockchain in modern networks, as well as in-depth studies on cybersecurity challenges and multidisciplinary methods in modern blockchain networks. Readers will find mathematical equations throughout the book as part of the underlying concepts and foundational methods, especially the complex algorithms involved in blockchain security aspects for hashing, coding, and decoding. This book also provides readers with the most in-depth technical guide to the intersection of computational intelligence and blockchain, two of the most important technologies for the development of next-generation complex systems

Artificial Intelligence for Medicine

• 1st Edition
• March 14, 2024
• Shai Ben- David + 5 more
• English
• Paperback 978-0-443-13671-9

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• eBook 978-0-443-13672-6

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Artificial Intelligence for Medicine: An Applied Reference for Methods and Applications introduces readers to the methodology and AI/ML algorithms as well as cutting-edge applications to medicine, such as cancer, precision medicine, critical care, personalized medicine, telemedicine, drug discovery, molecular characterization, and patient mental health. Research in medicine and tailored clinical treatment are being quickly transformed by artificial intelligence (AI) and machine learning (ML). The content in this book is tailored to the reader's needs in terms of both type and fundamentals. It covers the current ethical issues and potential developments in this field.This book will be beneficial for academics, professionals in the IT industry, educators, students, and anyone else involved in the use and development of AI in the medical field.

Machine Learning with Noisy Labels

• 1st Edition
• February 23, 2024
• Gustavo Carneiro
• English
• Paperback 978-0-443-15441-6

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• eBook 978-0-443-15442-3

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Machine Learning and Noisy Labels: Definitions, Theory, Techniques and Solutions provides an ideal introduction to machine learning with noisy labels that is suitable for senior undergraduates, post graduate students, researchers and practitioners using, and researching, machine learning methods. Most of the modern machine learning models based on deep learning techniques depend on carefully curated and cleanly labeled training sets to be reliably trained and deployed. However, the expensive labeling process involved in the acquisition of such training sets limits the number and size of datasets available to build new models, slowing down progress in the field. This book defines the different types of label noise, introduces the theory behind the problem, presents the main techniques that enable the effective use of noisy-label training sets, and explains the most accurate methods.

Intelligent Learning Approaches for Renewable and Sustainable Energy

• 1st Edition
• February 21, 2024
• Josep M. Guerrero + 3 more
• English
• Paperback 978-0-443-15806-3

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• eBook 978-0-443-15807-0

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Intelligent Learning Approaches for Renewable and Sustainable Energy provides a practical, systematic overview of the application of advanced intelligent control techniques, adaptive techniques, machine learning algorithms, and predictive control in renewable and sustainable energy. Sections introduce intelligent learning approaches and the roles of artificial intelligence and machine learning in terms of energy and sustainability, grid transformation, large-scale integration of renewable energy, and variability and flexibility of renewable sources. Other sections provide detailed coverage of intelligent learning techniques as applied to key areas of renewable and sustainable energy, including forecasting, supply and demand, integration, energy management, optimization, and more.This is a useful resource for researchers, scientists, advanced students, energy engineers, R&D professionals, and other industrial personnel with an interest in sustainable energy and integration of renewable energy sources, energy systems, energy engineering, machine learning, and artificial intelligence.

Synthetic Data and Generative AI

• 1st Edition
• January 9, 2024
• Vincent Granville
• English
• Paperback 978-0-443-21857-6

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• eBook 978-0-443-21856-9

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Synthetic Data and Generative AI covers the foundations of machine learning with modern approaches to solving complex problems and the systematic generation and use of synthetic data. Emphasis is on scalability, automation, testing, optimizing, and interpretability (explainable AI). For instance, regression techniques – including logistic and Lasso – are presented as a single method without using advanced linear algebra. Confidence regions and prediction intervals are built using parametric bootstrap without statistical models or probability distributions. Models (including generative models and mixtures) are mostly used to create rich synthetic data to test and benchmark various methods.

Connectomic Medicine

• 1st Edition
• December 1, 2023
• Michael E. Sughrue + 2 more
• English
• Paperback 978-0-443-19089-6

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• eBook 978-0-443-19090-2

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Connectomic Medicine: A Guide to Brain AI in Treatment Decision Planning examines how to apply connectomics to clinical medicine, including discussions on techniques, applications, novel ideas, and in case examples that highlight the state-of-the-art. Written by pioneers, this volume serves as the foundation for all neuroscience clinicians/researchers venturing into the field of AI medicine, its realistic applications, and how to integrate AI connectomics into clinical practice. With widespread applications in neurology, neurosurgery and psychiatry, this book is appropriate for anyone interested in cerebral network anatomy, imaging techniques, and insights into this emerging field.

Practical Design and Applications of Medical Devices

• 1st Edition
• November 24, 2023
• Dilber Uzun Ozsahin + 1 more
• English
• Paperback 978-0-443-14133-1

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• eBook 978-0-443-14132-4

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Practical Design and Applications of Medical Devices focuses on devices which receive and transmit bioelectric signals, such as electrocardiograph, electrodes, blood flow, blood pressure, physiological effects and, in some cases, current flowing through the human body. This thorough guide for researchers and engineers in the field of biomedical and instrumentation engineering presents a streamlined medical strategy for designing these medical devices, sensors, and tools. It also promotes operational efficiency in the healthcare industry, with the goals of improving patient safety, lowering overall healthcare costs, broadening access to healthcare services, and improving accessibility.

Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images

• 1st Edition
• November 16, 2023
• D. Jude Hemanth
• English
• Paperback 978-0-443-13999-4

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• eBook 978-0-443-14000-6

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Computational Intelligence and Modelling Techniques for Disease Detection in Mammogram Images comprehensively examines the wide range of AI-based mammogram analysis methods for medical applications. Beginning with an introductory overview of mammogram data analysis, the book covers the current technologies such as ultrasound, molecular breast imaging (MBI), magnetic resonance (MR), and Positron Emission mammography (PEM), as well as the recent advancements in 3D breast tomosynthesis and 4D mammogram. Deep learning models are presented in each chapter to show how they can assist in the efficient processing of breast images.The book also discusses hybrid intelligence approaches for early-stage detection and the use of machine learning classifiers for cancer detection, staging and density assessment in order to develop a proper treatment plan. This book will not only aid computer scientists and medical practitioners in developing a real-time AI based mammogram analysis system, but also addresses the issues and challenges with the current processing methods which are not conducive for real-time applications.