Books in Artificial intelligence general

51-60 of 102 results in All results

Blockchain Applications for Healthcare Informatics

• 1st Edition
• May 20, 2022
• Sudeep Tanwar
• English
• Paperback 978-0-323-90615-9

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• eBook 978-0-323-90829-0

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Blockchain Applications for Healthcare Informatics: Beyond 5G offers a comprehensive survey of 5G-enabled technology in healthcare applications. This book investigates the latest research in blockchain technologies and seeks to answer some of the practical and methodological questions surrounding privacy and security in healthcare. It explores the most promising aspects of 5G for healthcare industries, including how hospitals and healthcare systems can do better. Chapters investigate the detailed framework needed to maintain security and privacy in 5G healthcare services using blockchain technologies, along with case studies that look at various performance evaluation metrics, such as privacy preservation, scalability and healthcare legislation.

Tactile Sensing, Skill Learning, and Robotic Dexterous Manipulation

• 1st Edition
• April 2, 2022
• Qiang Li + 4 more
• English
• Paperback 978-0-323-90445-2

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• eBook 978-0-323-90417-9

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Tactile Sensing, Skill Learning and Robotic Dexterous Manipulation focuses on cross-disciplinary lines of research and groundbreaking research ideas in three research lines: tactile sensing, skill learning and dexterous control. The book introduces recent work about human dexterous skill representation and learning, along with discussions of tactile sensing and its applications on unknown objects’ property recognition and reconstruction. Sections also introduce the adaptive control schema and its learning by imitation and exploration. Other chapters describe the fundamental part of relevant research, paying attention to the connection among different fields and showing the state-of-the-art in related branches. The book summarizes the different approaches and discusses the pros and cons of each. Chapters not only describe the research but also include basic knowledge that can help readers understand the proposed work, making it an excellent resource for researchers and professionals who work in the robotics industry, haptics and in machine learning.

Artificial Intelligence and Data Science in Environmental Sensing

• 1st Edition
• February 9, 2022
• Mohsen Asadnia + 2 more
• English
• Paperback 978-0-323-90508-4

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• eBook 978-0-323-90507-7

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Artificial Intelligence and Data Science in Environmental Sensing provides state-of-the-art information on the inexpensive mass-produced sensors that are used as inputs to artificial intelligence systems. The book discusses the advances of AI and Machine Learning technologies in material design for environmental areas. It is an excellent resource for researchers and professionals who work in the field of data processing, artificial intelligence sensors and environmental applications.

Deep Learning for Robot Perception and Cognition

• 1st Edition
• February 4, 2022
• Alexandros Iosifidis + 1 more
• English
• Paperback 978-0-323-85787-1

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• eBook 978-0-323-88572-0

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Deep Learning for Robot Perception and Cognition introduces a broad range of topics and methods in deep learning for robot perception and cognition together with end-to-end methodologies. The book provides the conceptual and mathematical background needed for approaching a large number of robot perception and cognition tasks from an end-to-end learning point-of-view. The book is suitable for students, university and industry researchers and practitioners in Robotic Vision, Intelligent Control, Mechatronics, Deep Learning, Robotic Perception and Cognition tasks.

Deep Learning on Edge Computing Devices

• 1st Edition
• February 2, 2022
• Xichuan Zhou + 3 more
• English
• Paperback 978-0-323-85783-3

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• eBook 978-0-323-90927-3

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Deep Learning on Edge Computing Devices: Design Challenges of Algorithm and Architecture focuses on hardware architecture and embedded deep learning, including neural networks. The title helps researchers maximize the performance of Edge-deep learning models for mobile computing and other applications by presenting neural network algorithms and hardware design optimization approaches for Edge-deep learning. Applications are introduced in each section, and a comprehensive example, smart surveillance cameras, is presented at the end of the book, integrating innovation in both algorithm and hardware architecture. Structured into three parts, the book covers core concepts, theories and algorithms and architecture optimization.This book provides a solution for researchers looking to maximize the performance of deep learning models on Edge-computing devices through algorithm-hardware co-design.

Artificial Intelligence for Healthcare Applications and Management

• 1st Edition
• January 13, 2022
• Boris Galitsky + 1 more
• English
• Paperback 978-0-12-824521-7

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• eBook 978-0-12-824522-4

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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 978-0-323-85214-2

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• eBook 978-0-323-90362-2

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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 978-0-12-823818-9

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• eBook 978-0-12-823819-6

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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.

Cognitive Data Models for Sustainable Environment

• 1st Edition
• September 19, 2021
• Siddhartha Bhattacharyya + 4 more
• English
• Paperback 978-0-12-824038-0

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• eBook 978-0-12-824039-7

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Cognitive Models for Sustainable Environment reviews the fundamental concepts of gathering, processing and analyzing data from batch processes, along with a review of intelligent and cognitive tools that can be used. The book is centered on evolving novel intelligent/cognitive models and algorithms to develop sustainable solutions for the mitigation of environmental pollution. It unveils intelligent and cognitive models to address issues related to the effective monitoring of environmental pollution and sustainable environmental design. As such, the book focuses on the overall well-being of the global environment for better sustenance and livelihood. The book covers novel cognitive models for effective environmental pollution data management at par with the standards laid down by the World Health Organization. Every chapter is supported by real-life case studies, illustrative examples and video demonstrations that enlighten readers.

Mobile Edge Artificial Intelligence

• 1st Edition
• August 7, 2021
• Yuanming Shi + 3 more
• English
• Paperback 978-0-12-823817-2

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• eBook 978-0-12-823835-6

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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.