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Robotic Vision: Technologies for Machine Learning and Vision Applications

Robotic Vision: Technologies for Machine Learning and Vision Applications

Copyright: © 2013 |Pages: 535
ISBN13: 9781466626720|ISBN10: 1466626720|EISBN13: 9781466627031
DOI: 10.4018/978-1-4666-2672-0
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MLA

Garcia-Rodriguez, Jose, and Miguel A. Cazorla Quevedo, editors. Robotic Vision: Technologies for Machine Learning and Vision Applications. IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2672-0

APA

Garcia-Rodriguez, J. & Cazorla Quevedo, M. A. (Eds.). (2013). Robotic Vision: Technologies for Machine Learning and Vision Applications. IGI Global. https://doi.org/10.4018/978-1-4666-2672-0

Chicago

Garcia-Rodriguez, Jose, and Miguel A. Cazorla Quevedo, eds. Robotic Vision: Technologies for Machine Learning and Vision Applications. Hershey, PA: IGI Global, 2013. https://doi.org/10.4018/978-1-4666-2672-0

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Robotic systems consist of object or scene recognition, vision-based motion control, vision-based mapping, and dense range sensing, and are used for identification and navigation. As these computer vision and robotic connections continue to develop, the benefits of vision technology including savings, improved quality, reliability, safety, and productivity are revealed.

Robotic Vision: Technologies for Machine Learning and Vision Applications is a comprehensive collection which highlights a solid framework for understanding existing work and planning future research. This book includes current research on the fields of robotics, machine vision, image processing and pattern recognition that is important to applying machine vision methods in the real world.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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List of Reviewers
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Foreword
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Preface
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Acknowledgment
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Chapters
Chapter 1
Computer Vision  (pages 23-24)
Computer Vision
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Chapter 2
Computer Vision Applications
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Chapter 3
3D Computer Vision and Robotics
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Chapter 4
Social Robotics  (pages 210-210)
Social Robotics
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Chapter 5
Vision Control  (pages 302-302)
Vision Control
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Chapter 6
Visual Attention  (pages 371-371)
Visual Attention
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Back Materials
Compilation of References
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About the Contributors
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Index
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