Title :
Back-Propagation and K-Means Algorithms Comparison
Author :
Skorpil, Vladislav ; Stastny, Jiri
Author_Institution :
Dept. of Telecommun., Brno Univ. of Technol.
Abstract :
The paper describes the application of algorithms for object classification by using artificial neural networks. The MLP (multi layer perceptron) and RBF (radial basis function) neural networks were used. We compared results obtained by a using of learning algorithms back-propagation (BP) and K-means. The real technological scene for object classification was simulated with digitization of two-dimensional pictures. The principles and algorithms given below have been used in an application that was developed at Brno University of Technology
Keywords :
backpropagation; image classification; multilayer perceptrons; radial basis function networks; K-means algorithms comparison; MLP; RBF; artificial neural networks; back-propagation; multi layer perceptron; object classification; radial basis function; two-dimensional pictures digitization; Artificial neural networks; Automation; Backpropagation algorithms; Computer networks; Computer science; Computer vision; Iterative algorithms; Neural networks; Neurons; Shape;
Conference_Titel :
Signal Processing, 2006 8th International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-9736-3
Electronic_ISBN :
0-7803-9736-3
DOI :
10.1109/ICOSP.2006.345838
