Title :
Hierarchies of autoassociators
Author :
Weingessel, A. ; Bischof, H. ; Hornik, K.
Author_Institution :
Inst. fur Statistik und Wahrscheinlichkeitstheorie, Tech. Univ. Wien, Austria
Abstract :
The principal component pyramid is a hierarchical neural network which can successfully be employed in image compression and feature extraction of images. Previously, the construction of the network from the corresponding pyramid was done on a case by case basis. In this paper we automate this process by giving formulas describing the size of the network and the number of weight constraints in the net
Keywords :
associative processing; data compression; feature extraction; image processing; network topology; neural nets; autoassociators; feature extraction; hierarchical neural network; image compression; network size; network topology; principal component pyramid; weight constraints; Feature extraction; Filtering; Image analysis; Image coding; Image sampling; Network topology; Neural networks; Principal component analysis;
Conference_Titel :
Pattern Recognition, 1996., Proceedings of the 13th International Conference on
Conference_Location :
Vienna
Print_ISBN :
0-8186-7282-X
DOI :
10.1109/ICPR.1996.547415
