Grouping variables in an underdetermined system for invariant object recognition
- Poster presentation: Introduction We study the problem of object recognition invariant to transformations, such as translation, rotation and scale. A system is underdetermined if its degrees of freedom (number of possible transformations and potential objects) exceed the available information (image size). The regularization theory solves this problem by adding constraints [1]. It is unclear what constraints biological systems use. We suggest that rather than seeking constraints, an underdetermined system can make decisions based on available information by grouping its variables. We propose a dynamical system as a minimum system for invariant recognition to demonstrate this strategy. ...
Author: | Jianhui Zhu, Christoph von der Malsburg |
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URN: | urn:nbn:de:hebis:30-70830 |
DOI: | https://doi.org/10.1186/1471-2202-10-S1-P308 |
Parent Title (English): | BMC neuroscience |
Document Type: | Article |
Language: | English |
Year of Completion: | 2009 |
Year of first Publication: | 2009 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2009/09/20 |
Volume: | 10(Suppl 1) |
Issue: | P308 |
Note: | © 2009 Zhu and Malsburg; licensee BioMed Central Ltd. |
Source: | from Eighteenth Annual Computational Neuroscience Meeting: CNS*2009 Berlin, Germany. 18–23 July 2009 |
HeBIS-PPN: | 218999771 |
Institutes: | Wissenschaftliche Zentren und koordinierte Programme / Frankfurt Institute for Advanced Studies (FIAS) |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
Sammlungen: | Sammlung Biologie / Sondersammelgebiets-Volltexte |
Licence (German): | Deutsches Urheberrecht |