Overview
- Presents some of the most recent research results in the area of machine learning and robot perception
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 7)
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About this book
This book presents some of the most recent research results in the area of machine learning and robot perception. The chapters represent new ways of solving real-world problems. The book covers topics such as intelligent object detection, foveated vision systems, online learning paradigms, reinforcement learning for a mobile robot, object tracking and motion estimation, 3D model construction, computer vision system and user modelling using dialogue strategies. This book will appeal to researchers, senior undergraduate/postgraduate students, application engineers and scientists.
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Table of contents (8 chapters)
Bibliographic Information
Book Title: Machine Learning and Robot Perception
Editors: Bruno Apolloni, Ashish Ghosh, Ferda Alpaslan, Lakhmi Jain, Srikanta Patnaik
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/b137627
Publisher: Springer Berlin, Heidelberg
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer-Verlag Berlin Heidelberg 2005
Hardcover ISBN: 978-3-540-26549-8Published: 14 September 2005
Softcover ISBN: 978-3-642-06586-6Published: 02 January 2013
eBook ISBN: 978-3-540-32409-6Published: 15 August 2005
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: X, 354
Topics: Control, Robotics, Mechatronics, Artificial Intelligence