DocumentCode :
304702
Title :
Implementation and design of a new model of neural network with application to typographical character recognition
Author :
Gómez, J.M. ; López, O. ; Montes, M. ; Bota, S.A. ; Juvells, I. ; Herms, A.
Author_Institution :
Fac. de Fisica, Barcelona Univ., Spain
Volume :
1
fYear :
1996
fDate :
16-19 Sep 1996
Firstpage :
201
Abstract :
Neural networks have received considerable attention during the lasts years, specially in the field of image recognition. On the other hand, error correcting codes are widely applied to the sampling system, transmission and storage of digital data. A new model of neural network has been developed, considering that a group of images can define a code. Also, an ASIC that is suitable for recognising a set or typographical characters has been designed. A description of the model, the basic architecture and the working modes of the designed circuit is presented
Keywords :
CMOS digital integrated circuits; application specific integrated circuits; character recognition; digital signal processing chips; error correction codes; image recognition; learning (artificial intelligence); neural chips; ASIC; CMOS technology; circuit architecture; data transmission; digital data storage; error correcting codes; image recognition; neural networks; sampling system; supervised learning; typographical character recognition; Application specific integrated circuits; Character recognition; Error correction; Error correction codes; Image recognition; Laboratories; Neural networks; Optical character recognition software; Optical computing; Optical materials;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing, 1996. Proceedings., International Conference on
Conference_Location :
Lausanne
Print_ISBN :
0-7803-3259-8
Type :
conf
DOI :
10.1109/ICIP.1996.560658
Filename :
560658
Link To Document :
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