Clustering is one of the main methods for getting insight on the underlying nature and
structure of data. The purpose of clustering is organizing a set of data into clusters, such that …

In this paper we propose a criterion to balance the processing time and the solution quality
of k-means cluster algorithms when applied to instances where the number n of objects is …

Image segmentation based on an adaptive K-means clustering algorithm is presented. The
proposed method tries to develop K-means algorithm to obtain high performance and …

Chronic wound (CW) treatment by large is a burden for the government and society due to
its high cost and time consuming treatment. It becomes more serious for the old age patient …

This paper proposes a new criterion for reducing the processing time of the assignment of
data points to clusters for algorithms of the k-means family, when they are applied to …

Due to explosion in the number of autonomous data sources, there is a growing need for
effective approaches to distributed clustering. This paper compares the performance of two …

In this paper, an enhanced version of the K-Means algorithm that incorporates a new
convergence criterion is presented. The largest centroid displacement at each iteration was …

Many measures to quantify the nonlinear dynamics of a time series are based on estimating
the probability of certain features from their relative frequencies. Once a normalised …

Image segmentation is typically used to locate objects and boundaries in images. The result
of image segmentation is a set of segments that collectively cover the entire image, or a set …

Chronic wound (CW) diagnosis is more demanding to monitor the healing process of the
wound. However, the availability of specialist medical help in remote/rural areas in …