An efficient digital architecture for character recognition

Author

Gioiello, M. ; Sorbello, F. ; Tarantino, A. ; Vassallo, G.

Author_Institution

Dipartimento di Ingegneria Elettrica, Palermo Univ., Italy

fYear

1995

fDate

18-20 Sep 1995

Firstpage

144

Lastpage

148

Abstract

We introduce a new digital neural architecture designed for automatic hand-written characters recognition. The architecture implements a two-layer perceptron off-line trained by conjugate gradient descent algorithm and the final weights are quantized and stored in a RAM. The architecture was developed and tested using the VHDL Alliance 2.0 CAD System simulator: it is easy to implement using standard VLSI technologies and may be used to deal with multi-level inputs

Keywords

character recognition; computer architecture; conjugate gradient methods; hardware description languages; neural net architecture; perceptrons; VHDL Alliance 2.0 CAD System simulator; automatic hand-written characters recognition; character recognition; conjugate gradient descent algorithm; digital architecture; multi-level inputs; neural architecture; two-layer perceptron; Character recognition; Chromium; Circuits; Databases; Design automation; Minimization; Multilayer perceptrons; NIST; Standards development; System testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Architectures for Machine Perception, 1995. Proceedings. CAMP '95

Conference_Location

Como

Print_ISBN

0-8186-7134-3

Type

conf

DOI

10.1109/CAMP.1995.521031

Filename

521031

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3061418