DocumentCode
2554052
Title
Particle Swarm Optimisation and Self Organising Maps Based Image Classifier
Author
Chandramouli, Krishna
Author_Institution
Univ. of London, London
fYear
2007
fDate
17-18 Dec. 2007
Firstpage
225
Lastpage
228
Abstract
Neural network based image classification has been dominated by self organising maps. Following the recent developments in biologically inspired optimisation techniques, the application of particle swarm optimization algorithm for updating the weights of self organising maps has been studied in this paper, along with different network configurations of self organising maps. Experimental results are presented for 6 different classes from the Corel database based on MPEG -7 visual descriptor.
Keywords
image classification; particle swarm optimisation; self-organising feature maps; visual databases; Corel database; MPEG -7 visual descriptor; biologically inspired optimisation; image classification; image classifier; neural net; particle swarm optimisation; particle swarm optimization; self organising maps; Biological information theory; Biological system modeling; Birds; Educational institutions; Evolution (biology); Genetic programming; Image classification; Particle swarm optimization; Space exploration; Stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Semantic Media Adaptation and Personalization, Second International Workshop on
Conference_Location
Uxbridge
Print_ISBN
0-7695-3040-0
Type
conf
DOI
10.1109/SMAP.2007.18
Filename
4414414
Link To Document