A survey on the development of self-organizing maps for unsupervised intrusion detection

X Qu, L Yang, K Guo, L Ma, M Sun, M Ke… - Mobile networks and …, 2021‏ - Springer
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 …

Binning sequences using very sparse labels within a metagenome

CKK Chan, AL Hsu, SK Halgamuge, SL Tang - BMC bioinformatics, 2008‏ - Springer
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 …

An unsupervised hierarchical dynamic self-organizing approach to cancer class discovery and marker gene identification in microarray data

AL Hsu, SL Tang, SK Halgamuge - Bioinformatics, 2003‏ - academic.oup.com
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 …

Using growing self‐organising maps to improve the binning process in environmental whole‐genome shotgun sequencing

CKK Chan, AL Hsu, SL Tang… - BioMed Research …, 2008‏ - Wiley Online Library
Metagenomic projects using whole‐genome shotgun (WGS) sequencing produces many
unassembled DNA sequences and small contigs. The step of clustering these sequences …

Dimensionality reduction for visualizing high-dimensional biological data

T Malepathirana, D Senanayake, R Vidanaarachchi… - Biosystems, 2022‏ - Elsevier
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 …

A directed batch growing approach to enhance the topology preservation of self-organizing map

M Vasighi, H Amini - Applied Soft Computing, 2017‏ - Elsevier
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 …

Smart motion detection sensor based on video processing using self-organizing maps

F Ortega-Zamorano, MA Molina-Cabello… - Expert Systems with …, 2016‏ - Elsevier
Most current approaches to computer vision are based on expensive, high performance
hardware to meet the heavy computational requirements of the employed algorithms. These …

Structure in the Three-dimensional galaxy distribution. I. Methods and example results

MJ Way, PR Gazis, JD Scargle - The Astrophysical Journal, 2010‏ - iopscience.iop.org
Three methods for detecting and characterizing structure in point data, such as that
generated by redshift surveys, are described: classification using self-organizing maps …

[HTML][HTML] Large-scale map** of carbon stocks in riparian forests with self-organizing maps and the k-nearest-neighbor algorithm

L Suchenwirth, W Stümer, T Schmidt, M Förster… - Forests, 2014‏ - mdpi.com
Among the machine learning tools being used in recent years for environmental applications
such as forestry, self-organizing maps (SOM) and the k-nearest neighbor (kNN) algorithm …

Bregman divergences for growing hierarchical self-organizing networks

E Lopez-Rubio, EJ Palomo… - International Journal of …, 2014‏ - World Scientific
Growing hierarchical self-organizing models are characterized by the flexibility of their
structure, which can easily accomodate for complex input datasets. However, most …