Publication Details

Handwritten Digits Recognition Improved by Multiresolution Classifier Fusion

ŠTRBA Miroslav, HEROUT Adam and HAVEL Jiří. Handwritten Digits Recognition Improved by Multiresolution Classifier Fusion. In: Proceedings of IbPRIA 2011, LNCS. Berlin: Springer Verlag, 2011, pp. 726-733. ISBN 978-3-642-21256-7.
Czech title
Rozpoznávání ručně psaných číslic vylepšeno fúzí klasifikátorů v různých rozlišeních
Type
conference paper
Language
english
Authors
Štrba Miroslav, Ing. (FIT BUT)
Herout Adam, prof. Ing., Ph.D. (DCGM FIT BUT)
Havel Jiří, Ing., Ph.D. (DCGM FIT BUT)
Keywords

Digit Recognition, Classifier Fusion, Multiresolution

Abstract

One common approach to construction of highly accurate classifiers for hadwritten digit recognition is fusion of several weaker classifiers into a compound one, which (when meeting some constraints) outperforms all the individual fused classifiers.  This paper studies the possibility of fusing classifiers of different kinds (Self-Organizing Maps, Randomized Trees, and AdaBoost with MB-LBP weak hypotheses) constructed on training sets resampled to different resolutions.  While it is common to select one resolution of the input samples as the ``ideal one'' and fuse classifiers constructed for it, this paper shows that the accuracy of classification can be improved by fusing information from several scales.

Published
2011
Pages
726-733
Proceedings
Proceedings of IbPRIA 2011, LNCS
Conference
Iberian Conference on Pattern Recognition and Image Analysis, Las Palmas de Gran Canaria, ES
ISBN
978-3-642-21256-7
Publisher
Springer Verlag
Place
Berlin, DE
BibTeX 
@INPROCEEDINGS{FITPUB9508,
   author = "Miroslav \v{S}trba and Adam Herout and Ji\v{r}\'{i} Havel",
   title = "Handwritten Digits Recognition Improved by Multiresolution Classifier Fusion",
   pages = "726--733",
   booktitle = "Proceedings of IbPRIA 2011, LNCS",
   year = 2011,
   location = "Berlin, DE",
   publisher = "Springer Verlag",
   ISBN = "978-3-642-21256-7",
   language = "english",
   url = "https://www.fit.vut.cz/research/publication/9508"
}
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