Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

A novel self-organizing neural network for defect image classification

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
2 Author(s)
Pakkanen, J. ; Laboratory of Comput. & Information Sci., Helsinki Univ. of Technol., Finland ; Iivarinen, J.

A novel self-organizing neural network called the evolving tree is applied to classification of defect images. The evolving tree resembles the self-organizing map (SOM) but it has several advantages over the SOM. Experiments present a comparison between a normal SOM, a supervised SOM, and the evolving tree algorithm for classification of defect images that are taken from a real web inspection system. The MPEG-7 standard feature descriptors are applied. The results show that the evolving tree provides better classification accuracies and reduced computational costs over the normal SOMs.

Published in:

Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on  (Volume:4 )

Date of Conference:

25-29 July 2004