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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Table of contents (8 chapters)
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Front Matter
Keywords
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.
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