Publication detail

Back-Propagation and K-Means Algorithms Comparison

ŠKORPIL, V. ŠŤASTNÝ, J.

Original Title

Back-Propagation and K-Means Algorithms Comparison

Type

conference paper

Language

English

Original 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

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

Authors

ŠKORPIL, V.; ŠŤASTNÝ, J.

RIV year

2006

Released

17. 11. 2006

Publisher

IEEE Press

Location

Beijing, China

ISBN

0-7803-9736-3

Book

2006 8th International Conference on SIGNAL PROCESSING Proceedings

Edition

,2006 8th International Conference on SIGNAL PROCESSING Proceedings,Volume III of IV

Edition number

1

Pages from

1871

Pages to

1874

Pages count

4

BibTex

@inproceedings{BUT21879,
  author="Vladislav {Škorpil} and Jiří {Šťastný}",
  title="Back-Propagation and K-Means Algorithms Comparison",
  booktitle="2006 8th International Conference on SIGNAL PROCESSING Proceedings",
  year="2006",
  series=",2006 8th International Conference on SIGNAL PROCESSING Proceedings,Volume III of IV",
  number="1",
  pages="4",
  publisher="IEEE Press",
  address="Beijing, China",
  isbn="0-7803-9736-3"
}