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ICMCS
2007
IEEE
194views Multimedia» more  ICMCS 2007»
15 years 6 months ago
Automatically Tuning Background Subtraction Parameters using Particle Swarm Optimization
A common trait of background subtraction algorithms is that they have learning rates, thresholds, and initial values that are hand-tuned for a scenario in order to produce the des...
Brandyn White, Mubarak Shah
GECCO
2007
Springer
210views Optimization» more  GECCO 2007»
15 years 6 months ago
Markov chain models of bare-bones particle swarm optimizers
We apply a novel theoretical approach to better understand the behaviour of different types of bare-bones PSOs. It avoids many common but unrealistic assumptions often used in an...
Riccardo Poli, William B. Langdon
ASC
2010
14 years 12 months ago
Simplifying Particle Swarm Optimization
The general purpose optimization method known as Particle Swarm Optimization (PSO) has received much attention in past years, with many attempts to find the variant that performs ...
M. E. H. Pedersen, Andrew J. Chipperfield
ICPR
2008
IEEE
15 years 6 months ago
Comparison of Particle Swarm Optimization and Genetic Algorithm for HMM training
Hidden Markov Model (HMM) is the dominant technology in speech recognition. The problem of optimizing model parameters is of great interest to the researchers in this area. The Ba...
Fengqin Yang, Changhai Zhang, Tieli Sun
PRL
2010
188views more  PRL 2010»
14 years 6 months ago
A fast divisive clustering algorithm using an improved discrete particle swarm optimizer
As an important technique for data analysis, clustering has been employed in many applications such as image segmentation, document clustering and vector quantization. Divisive cl...
Liang Feng, Ming-Hui Qiu, Yu-Xuan Wang, Qiao-Liang...