Authors:
- Focuses on building bridges between natural and artificial computation
- Presents an object identification model and two different strategies for online learning
- Evaluates using a realistic scenario and delivers convincing results
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Table of contents (16 chapters)
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Front Matter
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Unsupervised Learning
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Front Matter
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Supervised Learning and Semi-supervised Learning
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Front Matter
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About this book
Authors and Affiliations
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School of Software Engineering, Xi’an Jiaotong University, Xi’an, China
Xiaochun Wang
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School of Information Engineering, Chang’an University, Xi’an, China
Xiali Wang
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Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, USA
Don Mitchell Wilkes
About the authors
Xia Li Wang received the PhD degree from the Department of Computer Science, Northwest University, China, in 2005. He is a faculty member in the Department of Computer Science, Changan University, China. His research interests are in computer vision, signal processing, intelligent traffic system, and pattern recognition.
D. Mitchell Wilkes received the BSEE degree from Florida Atlantic, and the MSEE and PhD degrees from Georgia Institute of Technology. His research interests include digital signal processing, image processing and computer vision, structurally adaptive systems, sonar,as well as signal modeling. He is a member of the IEEE and a faculty member at the Department of Electrical Engineering and Computer Science, Vanderbilt University. He is a member of the IEEE.
Bibliographic Information
Book Title: Machine Learning-based Natural Scene Recognition for Mobile Robot Localization in An Unknown Environment
Authors: Xiaochun Wang, Xiali Wang, Don Mitchell Wilkes
DOI: https://doi.org/10.1007/978-981-13-9217-7
Publisher: Springer Singapore
eBook Packages: Intelligent Technologies and Robotics, Intelligent Technologies and Robotics (R0)
Copyright Information: Xi'an Jiaotong University Press 2020
Hardcover ISBN: 978-981-13-9216-0Published: 24 August 2019
Softcover ISBN: 978-981-13-9219-1Published: 25 August 2020
eBook ISBN: 978-981-13-9217-7Published: 12 August 2019
Edition Number: 1
Number of Pages: XXII, 328
Number of Illustrations: 21 b/w illustrations, 78 illustrations in colour
Topics: Robotics and Automation, Computer Imaging, Vision, Pattern Recognition and Graphics, Computational Intelligence, Robotics, Machine Learning