Please use this identifier to cite or link to this item: http://elar.urfu.ru/handle/10995/50906
Title: Self-learning algorithm for visual recognition and object categorization for autonomous mobile robots
Authors: Gorbenko, Anna
Popov, Vladimir
Issue Date: 2012
Publisher: American Physical Society (APS)
Abstract: In order to execute tasks and to navigate in an environment, an autonomous mobile robot needs a complex visual system to cope with detection, characterization and recognition of places and objects. We are interested here in the development of detection and characterization functions, integrated on a robot. In this paper we consider an approach to the development of categorization systems based on building by a robot of its own semantics, which used only by the robot and is not designed for human perception. © 2012 Springer Science+Business Media B.V.
Keywords: GENETIC ALGORITHM
NEURAL NETWORK
VISUAL RECOGNITION AND OBJECT CATEGORIZATION
URI: http://elar.urfu.ru/handle/10995/50906
Conference name: International Conference on Computer, Informatics, Cybernetics and Applications 2011, CICA 2011
Conference date: 13.09.2011-16.09.2011
SCOPUS ID: 84855393354
PURE ID: 1098086
ISSN: 1876-1100
1876-1119
DOI: 10.1007/978-94-007-1839-5_139
Appears in Collections:Научные публикации ученых УрФУ, проиндексированные в SCOPUS и WoS CC

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