Classifying Three-way Seismic Volcanic Data by Dissimilarity Representation
| Autor: | Isneri Talavera, Robert P. W. Duin, Mauricio Orozco-Alzate, John Makario Londoño-Bonilla, Diana Porro-Muñoz |
|---|---|
| Rok vydání: | 2010 |
| Předmět: |
geography
Multivariate analysis geography.geographical_feature_category Computer science business.industry 020207 software engineering Pattern recognition 02 engineering and technology computer.software_genre Time–frequency analysis ComputingMethodologies_PATTERNRECOGNITION Volcano Three way 0202 electrical engineering electronic engineering information engineering Spectrogram 020201 artificial intelligence & image processing Data mining Artificial intelligence Representation (mathematics) business computer |
| Zdroj: | ICPR |
| Popis: | Multi-way data analysis is a multivariate data analysis technique having a wide application in some fields. Nevertheless, the development of classification tools for this type of representation is incipient yet. In this paper we study the dissimilarity representation for the classification of three-way data, as dissimilarities allow the representation of multi-dimensional objects in a natural way. As an example, the classification of seismic volcanic events is used. It is shown that in this application classification based on 2D spectrograms, dissimilarities perform better than on 1D spectral features. |
| Databáze: | OpenAIRE |
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