Cluster analysis is an essential tool in data mining. Several clustering algorithms have been
proposed and implemented, most of which are able to find good quality clustering results …

A reliable nuclei segmentation is still an open-ended problem, especially in the breast
cancer histology images. For the same, this paper proposes an intelligent gravitational …

The application of several swarm intelligence and evolutionary metaheuristic algorithms in
data clustering problems has in the past few decades gained wide popularity and …

In cluster analysis, the goal has always been to extemporize the best possible means of
automatically determining the number of clusters. However, because of lack of prior domain …

Today, fog computing is an emerging technology to support resource-constrained Internet of
Things (IoT) applications. The scalability, geographic distribution, and heterogeneity of edge …

Widespread use of various mobiles, social networks and IOT devices results into continuous
generation of the data, often leading to the formation of the big data. Sustainable grouping of …

Video piracy is a challenging issue in the modern world. Approximately 90\% 90% of newly
released films were illegally distributed around the world via the Internet. To overcome this …

The automated quantification of different cell structures available in histopathological
images is a challenging task due to the presence of complex background structures …

Metaheuristic algorithms have been hybridized with the standard K-means to address the
latter's challenges in finding a solution to automatic clustering problems. However, the …

Automatic clustering problems require clustering algorithms to automatically estimate the
number of clusters in a dataset. However, the classical K-means requires the specification of …