Abstract. Traditional clustering algorithms are based on one representation space, usually a vector space. However, in a variety of modern applications, multiple representations ex...
Karin Kailing, Hans-Peter Kriegel, Alexey Pryakhin...
Subspace clustering has attracted great attention due to its capability of finding salient patterns in high dimensional data. Order preserving subspace clusters have been proven to...
In the last decades, a number of robust fuzzy clustering algorithms have been proposed to partition data sets affected by noise and outliers. Robust fuzzy C-means (robust-FCM) is c...
Mario G. C. A. Cimino, Graziano Frosini, Beatrice ...
The detection of correlations between different features in a set of feature vectors is a very important data mining task because correlation indicates a dependency between the fe...
A robust video object segmentation algorithm for complex conditions in surveillance systems is proposed in this paper. This algorithm contains an unsupervised K-Means background c...