Back-Propagation and K-Means Algorithms Comparison

Back-Propagation and K-Means Algorithms Comparison

Stať ve sborníku v databázi WoS či Scopus

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.

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.

Image Processing, Back-Propagation Algorithm, K-Means Algorithm

ŠŤASTNÝ, J.; ŠKORPIL, V.

16.11.2006

The Chinese Institute of Electronics (CIE)

Guilin, China

International Conference on Signal Processing ICSP06

32P1-01

4