Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System
An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)
Editors: Lee, Sukhan, Ko, Hanseok, Oh, Songhwai (Eds.)
Free Preview- Presents recent research in multisensor fusion and integration for intelligent systems
- Includes selected papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017) held in Daegu, Korea, November 27–29, 2017
- Focuses on multisensor fusion and integration in the wake of big data, deep learning, and cyber physical systems
- Discusses how the multisensor fusion and integration technologies are applied to smart machines, which mark the beginning of things to things integration and human to machine integration
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- About this book
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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.
- Table of contents (17 chapters)
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Covariance Projection as a General Framework of Data Fusion and Outlier Removal
Pages 5-21
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State Estimation in Networked Control Systems with Delayed and Lossy Acknowledgments
Pages 22-38
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Performance of State Estimation and Fusion with Elliptical Motion Constraints
Pages 39-51
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Relevance and Redundancy as Selection Techniques for Human-Autonomy Sensor Fusion
Pages 52-75
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Classification of Reactor Facility Operational State Using SPRT Methods with Radiation Sensor Networks
Pages 76-97
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Table of contents (17 chapters)
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Bibliographic Information
- Bibliographic Information
-
- Book Title
- Multisensor Fusion and Integration in the Wake of Big Data, Deep Learning and Cyber Physical System
- Book Subtitle
- An Edition of the Selected Papers from the 2017 IEEE International Conference on Multisensor Fusion and Integration for Intelligent Systems (MFI 2017)
- Editors
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- Sukhan Lee
- Hanseok Ko
- Songhwai Oh
- Series Title
- Lecture Notes in Electrical Engineering
- Series Volume
- 501
- Copyright
- 2018
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing AG, part of Springer Nature
- eBook ISBN
- 978-3-319-90509-9
- DOI
- 10.1007/978-3-319-90509-9
- Hardcover ISBN
- 978-3-319-90508-2
- Series ISSN
- 1876-1100
- Edition Number
- 1
- Number of Pages
- VIII, 300
- Number of Illustrations
- 142 b/w illustrations
- Topics
