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To reduce the high dimensionality required for training of feature vectors in speaker identification, we propose an efficient GMM based on local PCA with Fuzzy clustering. The prop...
Clustering for the analysis of the gene expression profiles has been used for identifying the functions of the genes and of unknown genes. Since the genes usually belong to multipl...
— Fuzzy clustering methods have been widely used in many applications. These methods, including fuzzy k-means and Expectation Maximization, allow an object to be assigned to mult...
In fuzzy clustering, the fuzzy c-means (FCM) algorithm is the best known and most used method. Although FCM is a very useful method, it is sensitive to noise and outliers so that W...
Clustering belongs to the set of mathematical problems which aim at classification of data or objects into related sets or classes. Many different pattern clustering approaches bas...
Faezeh Ensan, Mohammad Hossien Yaghmaee, Ebrahim B...
Abstract—In contrast to standard fuzzy clustering, which optimizes a set of prototypes, one for each cluster, this paper studies fuzzy clustering without prototypes. Starting fro...
This paper deals with overlapping clustering, a trade off between crisp and fuzzy clustering. It has been motivated by recent applications in various domains such as information r...
With the wide diffusion of digital image acquisition devices,
the cost of managing hundreds of digital images is quickly increasing.
Currently, the main way to search digital ima...
This paper presents a novel method aimed to free form deformation
function approximation for purpose of image registration. The
method is currently feature-based. The algorithm i...
This paper presents a novel method for medical image registration.
The global transformation is obtained by composing affine transformations,
which are recovered locally from giv...