The self-organizing map (SOM) is a prominent neural network model that has found wide
application in a spectrum of domains. Accordingly, it has received widespread attention both …

Multi-view data has become fairly important since large amounts of information are
constantly generated from different sources. So far, most multi-view research on …

Głównym celem naukowym monografii jest opracowanie referencyjnej metodyki
prospektywnej analizy technologii, umożliwiającej dostarczenie wiedzy na temat: cech …

Featured Application A new algorithm that uses self-organizing maps and entropy calculus
to generate a tree structure based on XAI software principles. Abstract Data classification is …

Social vulnerability, from a socio-environmental point of view, focuses on the identification of
disadvantaged or vulnerable groups and the conditions and dynamics of the environments …

Years of research in the field of Pattern Recognition (PR) has led to scores of algorithms
which can achieve supervised pattern classification. Such algorithms assume the …

Due to climate change and expected food shortage in the coming decades, not only will it be
necessary to develop cultivars with greater tolerance to environmental stress, but it is also …

Kernel learning is becoming an important research topic in the area of machine learning,
and it has wide applications in pattern recognition, computer vision, image and signal …

This paper proposes two new batch SOM algorithms for dissimilarity data, namely RBSOM-
CWMdd and RBSOM-ACWMdd, both designed to give a crisp partition aiming to preserve …

Dimensionality reduction (DR) is a popular method in recognition and classification in many
areas, such as facial and medical imaging. In this paper, we propose a novel supervised DR …