Clustering is one of the powerful techniques that have been reached in image segmentation. The cluster analysis is to partition an image data set into number of disjoint groups or clusters. In …

We present a stochastic clustering algorithm which uses pairwise similarity of elements, based on a new graph theoretical algorithm for the sampling of cuts in graphs. The stochastic nature of …

Apr 1, 2013 · In this article, a novel image segmentation algorithm based on the theory of gravity, which is called as “stochastic feature based gravitational image segmentation algorithm …

Mar 1, 2021 · This paper proposes an image segmentation schema and presents two improved FCM-based algorithms. In the proposed algorithms, pixel relevance is measured by the …

We present a stochastic clustering algorithm which uses pairwise similarity of elements, based on a new graph the-oretical algorithm for the sampling of cuts in graphs. The stochastic nature of …

Oct 26, 2021 · Here, Stochastic Fractal Search (SFS) has been employed to find the optimal cluster centers. The experimental study has been performed over synthetic images, real-world …

Nov 1, 2001 · We present a stochastic clustering algorithm which uses pairwise similarity of elements and show how it can be used to address various problems in computer vision, …

We investigate the cluster validation problem associated with the use of a previously developed unsupervised segmentation algorithm based upon the expectation-maximization (EM) algorithm.

Dec 1, 2023 · Active learning with stochastic batches is efficient for medical image segmentation. Exploiting batch-level uncertainty improves conventional (sample-level) uncertainty-based AL …

ABSTRACT: We give a thorough analysis and comparison of various clustering techniques for pixel-based segmentation in this paper. Comparisons have been made between K-Means, the …