Abstract
Motivated by the outstanding performance of primates in pattern recognition tasks, the main purpose of this research is to exploit the behavioral and neuro-biological findings from primates’ visual perception mechanism for categorization applications. Dynamic Bio-Inspired Categorization system (DyBIC) is implemented utilizing nonlinear first order differential equations and its training phase can be accomplished online. The order of the set of differential equations is exclusively a function of the number of categories to be discriminated and the length of the feature vectors doesn’t affect system complexity. Besides, the proposed method carries out recognition in a multi-scale mode which is compatible with some of the well-known cognitive and neural phenomena like categorical perception and hierarchical discrimination. The performance of DyBIC is tested on a handmade typical classification example.
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Jamalabadi, H., Nasrollahi, H., Ahmadabadi, M.N., Araabi, B.N., Vahabie, A., Abolghasemi, M. (2012). A Dynamic Bio-inspired Model of Categorization. In: Huang, T., Zeng, Z., Li, C., Leung, C.S. (eds) Neural Information Processing. ICONIP 2012. Lecture Notes in Computer Science, vol 7664. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34481-7_20
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DOI: https://doi.org/10.1007/978-3-642-34481-7_20
Publisher Name: Springer, Berlin, Heidelberg
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