DocumentCode
298390
Title
Handwritten numerical recognition with neural networks and information fusion
Author
Cao, J. ; Shridhar, M. ; Ahmadi, M.
Author_Institution
Dept. of Electr. Eng., Windsor Univ., Ont., Canada
Volume
1
fYear
1994
fDate
3-5 Aug 1994
Firstpage
569
Abstract
Recently, in the area of character recognition, the concept of combining multiple classifiers has been proposed as a promising direction for the development of robust recognition systems. In this paper, an evidence fusion technique, based on the notion of fuzzy integral is utilized to obtain a reliable, high accuracy handwritten character recognition system. Experiments with a large real world data set reveal the robustness of this system
Keywords
character recognition; fuzzy logic; neural nets; pattern classification; character recognition system; evidence fusion technique; fuzzy integral; handwritten numerical recognition; information fusion; multiple classifiers; neural networks; real world data set; robust recognition systems; Density functional theory; Density measurement; Extraterrestrial measurements; Fuzzy neural networks; Fuzzy sets; Handwriting recognition; Integral equations; Neural networks; Q measurement; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location
Lafayette, LA
Print_ISBN
0-7803-2428-5
Type
conf
DOI
10.1109/MWSCAS.1994.519302
Filename
519302
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