Scalable multiresolution color image segmentation
Signal Processing
Kernel based automatic clustering using modified particle swarm optimization algorithm
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Automatic kernel clustering with a Multi-Elitist Particle Swarm Optimization Algorithm
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Intelligent Data Analysis
Automatic image pixel clustering with an improved differential evolution
Applied Soft Computing
Color video segmentation using fuzzy c-mean clustering with spatial information
WAV'09 Proceedings of the 3rd WSEAS international symposium on Wavelets theory and applications in applied mathematics, signal processing & modern science
Color video segmentation using Fuzzy C-mean clustering with spatial information
WSEAS Transactions on Signal Processing
Kernel-induced fuzzy clustering of image pixels with an improved differential evolution algorithm
Information Sciences: an International Journal
Journal of Network and Computer Applications
An auto-stopped hierarchical clustering algorithm integrating outlier detection algorithm
WAIM'05 Proceedings of the 6th international conference on Advances in Web-Age Information Management
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We propose in this communication an unsupervised clustering method called MLBG based upon the K-means algorithm. The originality of this method lies in the automatic determination of the number of clusters by calling into question an intermediate result. This method also enables to improve the different steps in the K-means algorithm. We show the efficiency of the MLBG method through some experimental results and we demonstrate the usefulness of the technique for image segmentation.