High performance OCR with syntactic neural networks

Author

Lucas, S.M.

Author_Institution

Essex Univ., Colchester, UK

fYear

1995

Firstpage

133

Lastpage

138

Abstract

This paper describes the application of a special type of syntactic neural network (SNN) to the recognition of hand-written digits. Importantly, it is shown that this class of SNN can be implemented to work at very high classification speeds (similar to that of an N-tuple classifier), but with higher classification accuracy when trained on enough data. Results are reported on the ESSEX and CEDAR data sets to demonstrate this

Keywords

image classification; neural nets; optical character recognition; CEDAR data set; ESSEX data set; N-tuple classifiers; classification accuracy; classification speed; handwritten digit recognition; high-performance OCR; optical character recognition; syntactic neural networks; training;

fLanguage

English

Publisher

iet

Conference_Titel

Artificial Neural Networks, 1995., Fourth International Conference on

Conference_Location

Cambridge

Print_ISBN

0-85296-641-5

Type

conf

DOI

10.1049/cp:19950542

Filename

497804

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=1621589