Image segmentation is the method of partitioning an image into a group of pixels that are
homogenous in some manner. The homogeneity dependents on some attributes like …

Image segmentation methodology is a part of nearly all computer schemes as a pre-
processing phase to excerpt more meaningful and useful information for analysing the …

In this article is introduced an improved version of Fast Fuzzy C-Means (FFCM) by using the
Crow Search optimization Algorithm (CSA) for the task of data clustering. In the proposed …

Most vehicle license plate recognition use neural network techniques to enhance its
computing capability. The image of the vehicle license plate is captured and processed to …

With the development of machine learning technologies, predicting stock movements by
analyzing news articles has been studied actively. Most of the existing studies utilize only …

In this paper we have used two fuzzy clustering algorithms, namely fuzzy c-means (FCM)
and Gustafson–Kessel clustering (GKC) along with local information for unsupervised …

Concrete is ubiquitous in the modern construction and building industry, bugholes are one
of the most typical imperfections on concrete surface, and traditional manual inspection …

This study aims to elucidate the process of crop evapotranspiration (ET c) and develop
models to estimate ET c as a crucial value to efficiently schedule irrigation. Accordingly, we …

Traditional two‐dimensional Otsu algorithm has several drawbacks; that is, the sum of
probabilities of target and background is approximate to 1 inaccurately, the details of …

Clustering has always been an exploratory but critical step in the knowledge discovery
process. Often unsupervised, the clustering task received a huge interest when reinforced by …