This paper describes a focused literature survey of self-organizing maps (SOM) in support of
intrusion detection. Specifically, the SOM architecture can be divided into two categories, ie …

Background In metagenomic studies, a process called binning is necessary to assign
contigs that belong to multiple species to their respective phylogenetic groups. Most of the …

Abstract Motivation: Current Self-Organizing Maps (SOMs) approaches to gene expression
pattern clustering require the user to predefine the number of clusters likely to be expected …

High throughput technologies used in experimental biological sciences produce data with a
vast number of variables at a rapid pace, making large volumes of high-dimensional data …

Metagenomic projects using whole-genome shotgun (WGS) sequencing produces many
unassembled DNA sequences and small contigs. The step of clustering these sequences …

Most current approaches to computer vision are based on expensive, high performance
hardware to meet the heavy computational requirements of the employed algorithms. These …

The growing self-organizing map (GSOM) possesses effective capability to generate feature
maps and visualizing high-dimensional data without pre-determining their size. Most of the …

Three methods for detecting and characterizing structure in point data, such as that
generated by redshift surveys, are described: classification using self-organizing maps …

Growing hierarchical self-organizing models are characterized by the flexibility of their
structure, which can easily accomodate for complex input datasets. However, most …

Abstract The original Self-Organizing Feature Map (SOFM) has been extended in many
ways to suit different goals and application domains. However, the topologies of the map …