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Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System, Sukhan Lee; Hanseok Ko; Songhwai Oh


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Автор: Sukhan Lee; Hanseok Ko; Songhwai Oh
Название:  Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System
ISBN: 9783030080303
Издательство: Springer
Классификация:




ISBN-10: 3030080307
Обложка/Формат: Soft cover
Страницы: 300
Вес: 0.47 кг.
Дата издания: 2018
Серия: Lecture Notes in Electrical Engineering
Язык: English
Издание: Softcover reprint of
Иллюстрации: 142 illustrations, black and white; viii, 300 p. 142 illus.
Размер: 234 x 156 x 17
Читательская аудитория: General (us: trade)
Основная тема: Engineering
Подзаголовок: An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)
Ссылка на Издательство: Link
Рейтинг:
Поставляется из: Германии
Описание: This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.


Multisensor Fusion and Integration for Intelligent Systems

Автор: Lee Suk-han; Hanseok Ko; Hernsoo Hahn
Название: Multisensor Fusion and Integration for Intelligent Systems
ISBN: 3642100570 ISBN-13(EAN): 9783642100574
Издательство: Springer
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Цена: 23508.00 р.
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Описание: This volume is aimed at engineers, researchers, educators, and advanced students in the field of Multisensor Fusion and Integration for Intelligent Systems. It includes the recent progress made in theory and applications.

Big Data Analytics for Cyber-Physical System in Smart City

Автор: Mohammed Atiquzzaman; Neil Yen; Zheng Xu
Название: Big Data Analytics for Cyber-Physical System in Smart City
ISBN: 9811525676 ISBN-13(EAN): 9789811525674
Издательство: Springer
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Цена: 69876.00 р.
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Описание: This book gathers a selection of peer-reviewed papers presented at the first Big Data Analytics for Cyber-Physical System in Smart City (BDCPS 2019) conference, held in Shengyang, China, on 28-29 December 2019.

Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System

Автор: Lee
Название: Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System
ISBN: 3319905082 ISBN-13(EAN): 9783319905082
Издательство: Springer
Рейтинг:
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book includes selected papers from the 13th IEEE International Conference on Multisensor Integration and Fusion for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 16–22, 2017. It covers various topics, including sensor/actuator networks, distributed and cloud architectures, bio-inspired systems and evolutionary approaches, methods of cognitive sensor fusion, Bayesian approaches, fuzzy systems and neural networks, biomedical applications, autonomous land, sea and air vehicles, localization, tracking, SLAM, 3D perception, manipulation with multifinger hands, robotics, micro/nano systems, information fusion and sensors, and multimodal integration in HCI and HRI. The book is intended for robotics scientists, data and information fusion scientists, researchers and professionals at universities, research institutes and laboratories.

Mathematical Techniques in Multisensor Data Fusion, Second Edition

Название: Mathematical Techniques in Multisensor Data Fusion, Second Edition
ISBN: 1580533353 ISBN-13(EAN): 9781580533355
Издательство: Artech House
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Цена: 25872.00 р.
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Описание: Since the publication of the first edition of this book, advances in algorithms, logic and software tools have transformed the field of data fusion. This edition covers these areas as well as smart agents, human computer interaction, cognitive aides to analysis and data system fusion control.

Multisensor data fusion

Название: Multisensor data fusion
ISBN: 1482263742 ISBN-13(EAN): 9781482263749
Издательство: Taylor&Francis
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Цена: 25265.00 р.
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Описание:

Multisensor Data Fusion: From Algorithms and Architectural Design to Applications covers the contemporary theory and practice of multisensor data fusion, from fundamental concepts to cutting-edge techniques drawn from a broad array of disciplines. Featuring contributions from the world's leading data fusion researchers and academicians, this authoritative book:

  • Presents state-of-the-art advances in the design of multisensor data fusion algorithms, addressing issues related to the nature, location, and computational ability of the sensors
  • Describes new materials and achievements in optimal fusion and multisensor filters
  • Discusses the advantages and challenges associated with multisensor data fusion, from extended spatial and temporal coverage to imperfection and diversity in sensor technologies
  • Explores the topology, communication structure, computational resources, fusion level, goals, and optimization of multisensor data fusion system architectures
  • Showcases applications of multisensor data fusion in fields such as medicine, transportation's traffic, defense, and navigation

Multisensor Data Fusion: From Algorithms and Architectural Design to Applications is a robust collection of modern multisensor data fusion methodologies. The book instills a deeper understanding of the basics of multisensor data fusion as well as a practical knowledge of the problems that can be faced during its execution.


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