Multilayer perceptron and uppercase handwritten characters recognition

Author

Bernard, Ir Gosselin

Author_Institution

Service de Theorie des Circuits et de Traitement du Signal, Fac. Polytech. de Mons, Belgium

fYear

1993

fDate

20-22 Oct 1993

Firstpage

935

Lastpage

938

Abstract

After an introduction to the problem of the automatic character recognition and on multilayer perceptron used for classification, the author describes what one can hope to get from a multilayer perceptron. Some of the problems that can occur during the training and present a fast learning algorithm are also described. This algorithm was tested to train a multilayer perceptron to recognize multiscriptor uppercase handwritten characters. The system has reached a recognition rate of 88.1%, without any contextual analysis, which is still indispensable, but will be easier due to the fact that the multilayer perceptron provides the probability of each class to be the unknown character

Keywords

character recognition; handwriting recognition; learning systems; multilayer perceptrons; pattern classification; automatic character recognition; classification; contextual analysis; fast learning algorithm; multilayer perceptron; multiscriptor uppercase handwritten characters; training; uppercase handwritten characters recognition; Character recognition; Circuits; Handwriting recognition; High performance computing; Multi-layer neural network; Multilayer perceptrons; Neural networks; Neurons; Performance analysis; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Document Analysis and Recognition, 1993., Proceedings of the Second International Conference on

Conference_Location

Tsukuba Science City

Print_ISBN

0-8186-4960-7

Type

conf

DOI

10.1109/ICDAR.1993.395583

Filename

395583