The aim of this work is to analyze the applicability of crowding differential evolution to unsupervised clustering. The basic idea of this approach, interpreting the clustering pr...
A split-and-merge framework based on a maximum variance criterion is proposed for disparity clustering. The proposed algorithm transforms low-level stereo disparity information to...
This paper describes unsupervised speech/speaker cluster validity measures based on a dissimilarity metric, for the purpose of estimating the number of clusters in a speech data s...
Kuntoro Adi, Kristine E. Sonstrom, Peter M. Scheif...
The goal of clustering is to identify distinct groups in a dataset. The basic idea of model-based clustering is to approximate the data density by a mixture model, typically a mix...
— An important consideration in clustering is the determination of the correct number of clusters and the appropriate partitioning of a given data set. In this paper, a newly dev...