DocumentCode :
2613728
Title :
Character recognition using neural based feature extractor and classifier
Author :
Cao, J. ; Ahmadi, M. ; Shridhar, M.
Author_Institution :
Dept. of Electr. Eng., Windsor Univ., Ont., Canada
fYear :
1993
fDate :
3-6 May 1993
Firstpage :
2442
Abstract :
The authors present a neural network architecture for the recognition of handwritten digits and machine printed multi-font characters. To reduce the dimension of the input data vector as well as robustness of the system, an appropriate neural net is utilized for the feature extraction part which is cascaded with another neural net for the classification purpose. The proposed architecture has been tested on a large sample of real field data and the results indicate the effectiveness of the proposed technique
Keywords :
character recognition; character sets; feature extraction; neural nets; pattern classification; classification; handwritten digits; input data vector; machine printed multi-font characters; neural based feature extractor; neural network architecture; robustness; Character recognition; Computer architecture; Data mining; Feature extraction; Handwriting recognition; Neural networks; Personal communication networks; Principal component analysis; Robustness; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-1281-3
Type :
conf
DOI :
10.1109/ISCAS.1993.394258
Filename :
394258
Link To Document :
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