Clustering is one of the most versatile tools for data analysis. In the recent years, clustering
that seeks the continuity of data (in opposition to classical centroid-based approaches) has …

This paper presents an experimental study on pedestrian classification and detection in far
infrared (FIR) images. The study includes an in-depth evaluation of several combinations of …

The graph clustering problem has become highly relevant due to the growing interest of
several research communities in social networks and their possible applications …

Data mining techniques are traditionally divided into two distinct disciplines depending on
the task to be performed by the algorithm: supervised learning and unsupervised learning …

In the past decades, neuroimaging of humans has gained a position of status within
neuroscience, and data-driven approaches and functional connectivity analyses of …

Prototype based classifiers are effective algorithms in modeling classification problems and
have been applied in multiple domains. While many supervised learning algorithms have …

Activity recognition requires further research to enable a multitude of human-centric
applications in the smart home environment. Currently, the major challenges in activity …

Prototype based learning offers an intuitive interface to inspect large quantities of electronic
data in supervised or unsupervised settings. Recently, many techniques have been …

In the family of Learning Classifier Systems, the classifier system XCS is most widely used
and investigated. However, the standard XCS has difficulties solving large multi-step …

In view of the fact that trunking communication system needs urgently to be developed
toward digital system in China, a design scheme of trunking communication system based …