Alex Tormási

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In this paper we present an improved version of the fuzzy based single-stroke character recognizer introduced in previous works. The modified recognition method is able to reach an acceptable accuracy in the character recognition with a significant decrease on the computational complexity of the algorithm. Different hierarchical rule-base techniques were(More)
In this paper we present two modified and improved versions of the formerly published Fuzzy-Based Single-Stroke Character Recognizer (FUBAR) algorithm. After introducing the original method, the study investigates the effects of two different improvements of the designed algorithm. The first extension is the use of symbol-dependent fuzzy grids to extract(More)
In this paper, the latest member of the FUzzy-BAsed character Recognizer (FUBAR) algorithm family with multi-stroke character support is presented. The paper summarizes the basic concept and development of multi-stroke FUBAR and compares the single-stroke, multi-stroke FUBAR algorithms with the most similar methods found in literature.
In this paper an extension for multi-stroke character recognition of FUzzy BAsed handwritten character Recognition (FUBAR) algorithm will be presented. First the basic concept of a single-stroke version will be overviewed; in the second part of the paper the new version of the algorithm with multi-stroke symbol support will be introduced, which deploy the(More)
In this paper a dynamic fuzzy rule weighting method (DFW) combined with evolutionary optimization are presented for the formerly published Fuzzy Based Single-Stroke Character Recognizer (FUBAR) method. With the introduced rule weighting technique the consequent parts of the if...then... rules are calculated similarly to the original FUBAR method, but a(More)
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