DocumentCode
3400978
Title
An evaluation study of traditional and neural network techniques for image processing applications
Author
Obaidat, M.S. ; Walk, J.V.
Author_Institution
Dept. of Electr. & Comput. Eng., Missouri-Columbia Univ., Independence, MO, USA
fYear
1991
fDate
14-17 May 1991
Firstpage
72
Abstract
A comparative study of the artificial neural computing and traditional approaches to image processing is performed. The major goal is to determine the usefulness of artificial neural systems (ANSs) for such image processing applications as histogramming and image encoding. The paradigm used was developed from a C programming language model of a perceptron ANS with consideration of backpropagation attributes. It is found that the ANS approach produces results similar to those of traditional techniques
Keywords
C language; backpropagation; image coding; neural nets; C programming language model; artificial neural computing; artificial neural systems; backpropagation attributes; histogramming; image encoding; image processing applications; neural network techniques; Application software; Associative memory; Backpropagation; Data mining; Image coding; Image processing; Image storage; Multilayer perceptrons; Neural networks; Random access memory;
fLanguage
English
Publisher
ieee
Conference_Titel
Circuits and Systems, 1991., Proceedings of the 34th Midwest Symposium on
Conference_Location
Monterey, CA
Print_ISBN
0-7803-0620-1
Type
conf
DOI
10.1109/MWSCAS.1991.252129
Filename
252129
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