In deep learning research, self-supervised learning (SSL) has received great attention,
triggering interest within both the computer vision and remote sensing communities. While …

The machine learning community has been overwhelmed by a plethora of deep learning--
based approaches. Many challenging computer vision tasks, such as detection, localization …

The partitional clustering concept started with K-means algorithm which was published in
1957. Since then many classical partitional clustering algorithms have been reported based …

Land-cover map** in remote sensing (RS) applications renders rich information for
decision support and environmental monitoring systems. The derivation of such information …

Gene expression data hide vital information required to understand the biological process
that takes place in a particular organism in relation to its environment. Deciphering the …

This paper describes a simulated annealing based multiobjective optimization algorithm that
incorporates the concept of archive in order to provide a set of tradeoff solutions for the …

This paper presents a survey of evolutionary algorithms designed for clustering tasks. It tries
to reflect the profile of this area by focusing more on those subjects that have been given …

With the rapid rise in the ubiquity and sophistication of Internet technology and the
accompanying growth in the number of network attacks, network intrusion detection has …

In cluster analysis, a fundamental problem is to determine the best estimate of the number of
clusters; this is known as the automatic clustering problem. Because of lack of prior domain …

With the ongoing development of Earth observation techniques, huge amounts of remote
sensing images with a high spectral-spatial-temporal resolution are now available, and have …