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ESANN
2008
13 years 6 months ago
Explaining Ant-Based Clustering on the basis of Self-Organizing Maps
Ant-based clustering is a nature-inspired technique whereas stochastic agents perform the task of clustering high-dimensional data. This paper analyzes the popular technique of Lum...
Lutz Herrmann, Alfred Ultsch
ANTSW
2008
Springer
13 years 5 months ago
The Architecture of Ant-Based Clustering to Improve Topographic Mapping
Abstract. This paper analyzes the popular ant-based clustering approach of Lumer/Faieta. Analysis of formulae unveils that ant-based clustering is strongly related to Kohonen’s S...
Lutz Herrmann, Alfred Ultsch
CIVR
2004
Springer
118views Image Analysis» more  CIVR 2004»
13 years 10 months ago
Use of Image Subset Features in Image Retrieval with Self-Organizing Maps
In content-based image retrieval (CBIR), the images in a database are indexed on the basis of low-level statistical features that can be automatically derived from the images. Due ...
Markus Koskela, Jorma Laaksonen, Erkki Oja
DIAL
2006
IEEE
167views Image Analysis» more  DIAL 2006»
13 years 10 months ago
Tree clustering for layout-based document image retrieval
We describe a system for the retrieval on the basis of layout similarity of document images belonging to collections stored in digital libraries. Layout regions are extracted and ...
Simone Marinai, Emanuele Marino, Giovanni Soda
ESANN
2004
13 years 6 months ago
Clustering functional data with the SOM algorithm
Abstract. In many situations, high dimensional data can be considered as sampled functions. We show in this paper how to implement a Self-Organizing Map (SOM) on such data by appro...
Fabrice Rossi, Brieuc Conan-Guez, Aïcha El Go...