Research on Unconstrained Handwritten Numeral Recognition by BP Feature Screening Based on Fuzzy Clustering

Pei Ye; Tao Jiang

doi:10.4028/www.scientific.net/AMM.734.504

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 734Research on Unconstrained Handwritten Numeral...

Research on Unconstrained Handwritten Numeral Recognition by BP Feature Screening Based on Fuzzy Clustering

Abstract:

In this paper, the recognition system of fuzzy clustering based on BP feature screening was put out. The figure specimens of experiment were filtered through BP network, and the result of screening was fit into the clustering source. At last fuzzy clustering was carried out by constituting the fuzzy relation matrix. The result of experiment demonstrates that this method has very high noise immunity capacity and overcame the limitation of traditional algorithm with single factor recognition. The recognition rate and precision ratio were greatly improved at the same time.

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Periodical:

Applied Mechanics and Materials (Volume 734)

Pages:

504-507

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.734.504

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Online since:

February 2015

Authors:

Pei Ye*, Tao Jiang

Keywords:

BP Neural Network, Digital Identification, Fuzzy Clustering

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