DocumentCode
284731
Title
A technique for defining the architecture and weights of a neural image classifier
Author
Re, R. ; Roli, F. ; Serpico, S.B. ; Vernazza, G.
Author_Institution
Dept. of Biophys. & Electron. Eng., Genoa Univ., Italy
Volume
2
fYear
1992
fDate
23-26 Mar 1992
Firstpage
401
Abstract
An approach to setting the architecture and the initial weights of an artificial neural network for solving classification problems is presented. A nonneural phase finds an approximate solution to the classification problems by constraining the shape of classification regions. After an appropriate mapping into a neural net, neural training is applied to refine the solution. Results on an image recognition application are presented
Keywords
image recognition; neural nets; artificial neural network; classification problems; image recognition; initial weights; mapping; neural image classifier; neural training; Artificial neural networks; Computer architecture; Fault tolerance; Image processing; Image recognition; Image restoration; Parallel processing; Shape; Sonar; Speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1992. ICASSP-92., 1992 IEEE International Conference on
Conference_Location
San Francisco, CA
ISSN
1520-6149
Print_ISBN
0-7803-0532-9
Type
conf
DOI
10.1109/ICASSP.1992.226035
Filename
226035
Link To Document