DocumentCode :
3105573
Title :
ANN-based handwritten character recognition
Author :
Hanmin, Huang ; Xiyue, Huang ; Ping, Zhang ; Yi, Chai ; Weiren, Shi
Author_Institution :
Inst. of Autom., Chongqing Univ., China
fYear :
1999
fDate :
36373
Firstpage :
1177
Lastpage :
1180
Abstract :
Based on an artificial neural network, digital image processing, and features extraction theory, the authors analyzed a BP network´s defect then presented improving solutions. In this paper, a new kind of handwritten character system has been constructed. Referring to the shortcoming of the traditional BP algorithm, a modified learning factor with adaptation is introduced, and a bizarre sample feature database is constructed for speeding up modified BP learning and classification. Experimental results show that the modified BP neural network algorithm (three layers forward, no feedback) can be used in handwritten character recognition, and satisfactory results have been obtained
Keywords :
backpropagation; feature extraction; feedforward neural nets; handwritten character recognition; multilayer perceptrons; ANN-based handwritten character recognition; adaptation; classification; digital image processing; modified BP neural network algorithm; modified learning factor; Automation; Biological neural networks; Brain; Character recognition; Cities and towns; Digital images; Fault tolerance; Feature extraction; Image analysis; Image databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SICE Annual, 1999. 38th Annual Conference Proceedings of the
Conference_Location :
Morioka
Print_ISBN :
4-907764-13-8
Type :
conf
DOI :
10.1109/SICE.1999.788719
Filename :
788719
Link To Document :
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