In this work, we use a copula-based approach to select the most important features for a
random forest classification. Based on associated copulas between these features, we carry …

A variety of remote sensing applications call for automatic optical classification of satellite
images. Recently, satellite missions, such as Sentinel-2, allow us to capture images in real …

Symbolic data analysis is an emerging field in statistics with great potential to become a
standard inferential technique. This research introduces a new approach to image feature …

This study introduces an innovative approach to image classification that uses Gaussian
copulas with an Empirical Cumulative Distribution Function (ECDF) approach. The strategic …

Wireless sensor networks (WSNs) find extensive applications in various sensitive domains
such as tracking, monitoring, environmental data collection and border surveillance. In these …

In prediction analysis, there may exist some nonlinear relations between the exploratory
variables, which are not captured by traditional correlation-based linear models such as …

This study uses elliptical copulas and transition probabilities for uncertainty modeling of
categorical spatial data. It begins by discussing the expressions of the cumulative …

Statistical pattern recognition has attracted great interest due to its applicability and to the
advances in technology and computing. Significant research has been done in areas such …

Nowadays, interest in technology is growing as technology advances and makes our jobs
easier. These rapid technological advancements bring with them a slew of unwanted …

Land use classification is fundamental both for monitoring and predicting regional
development patterns and for planning and regulating land use. This research proposed a …