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» Self-organizing maps and symbolic data
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KI
2007
Springer
14 years 2 months ago
Relational Neural Gas
Abstract. Prototype-based clustering algorithms such as the Self Organizing Map (SOM) or Neural Gas (NG) offer powerful tools for automated data inspection. The distribution of pr...
Barbara Hammer, Alexander Hasenfuss
JMM2
2008
92views more  JMM2 2008»
13 years 8 months ago
Dimensionality Reduction using SOM based Technique for Face Recognition
Unsupervised or Self-Organized learning algorithms have become very popular for discovery of significant patterns or features in the input data. The three prominent algorithms name...
Dinesh Kumar, C. S. Rai, Shakti Kumar
ICPR
2006
IEEE
14 years 9 months ago
Texture Edge Detection using Multi-resolution Features and SOM
Texture boundaries or edges are useful information for segmenting a texture image. We propose a texture edge detection algorithm using a bank of 1-D multi-channel, multiresolution...
Lalit Gupta, Sukhendu Das
ESANN
2006
13 years 9 months ago
Unsupervised clustering of continuous trajectories of kinematic trees with SOM-SD
We explore the capability of the Self Organizing Map for structured data (SOM-SD) to compress continuous time data recorded from a kinematic tree, which can represent a robot or an...
Jochen J. Steil, Risto Koiva, Alessandro Sperduti
HICSS
2006
IEEE
124views Biometrics» more  HICSS 2006»
14 years 2 months ago
Uncovering the Patterns in Pathology Ordering by Australian General Practitioners: A Data Mining Perspective
Pathology ordering by General Practitioners (GPs) is a significant contributor to rising health care costs both in Australia and worldwide. A thorough understanding of the nature ...
Zoe Yan Zhuang, Leonid Churilov, Ken Sikaris