ICIP 2006, Atlanta, GA
 

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Paper Detail

Paper:WP-P1.3
Session:Visual Object/Event Detection, Segmentation, and Classification
Time:Wednesday, October 11, 14:20 - 17:00
Presentation: Poster
Topic: Image & Video Segmentation: Clustering-based methods
Title: IMAGE CLASSIFICATION USING CHAOTIC PARTICLE SWARM OPTIMIZATION
Authors: Krishna Chandramouli; Queen Mary, University of London 
 Ebroul Izquierdo; Queen Mary, University of London 
Abstract: Particle Swarm Optimization is one of several meta-heuristic algorithms inspired by biological systems. The chaotic modeling of particle swarm optimization is presented in this paper with application to image classification. The performance of this modified particle swarm optimization algorithm is compared with standard particle swarm optimization. Numerical results of this comparative study are performed on binary classes of images from the Corel dataset.