7 February 1997 Mixed neural-traditional classifier for character recognition
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Proceedings Volume 2949, Imaging Sciences and Display Technologies; (1997) https://doi.org/10.1117/12.266360
Event: Advanced Imaging and Network Technologies, 1996, Berlin, Germany
Abstract
In this paper, we present the efficient voting classifier for the recognition of handwritten and printed characters. This system consists of three voting nonlinear classifiers: two of them based on the multilayer perceptron, and one uses the moments method. The combination of these kinds of systems shows superiority of neural techniques applied with classical against exclusive traditional approach and results in high percentage of correctly recognized characters. Also, we present a comparison of the recognition results.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Andrzej Stajniak, Andrzej Stajniak, Jaroslaw Szostakowski, Jaroslaw Szostakowski, Slawomir Skoneczny, Slawomir Skoneczny, } "Mixed neural-traditional classifier for character recognition", Proc. SPIE 2949, Imaging Sciences and Display Technologies, (7 February 1997); doi: 10.1117/12.266360; https://doi.org/10.1117/12.266360
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