Observatorio de I+D+i UPM

Memorias de investigación
Communications at congresses:
Visualizing and analysis of multispectral patterns using growing self-organizing maps
Year:2007
Research Areas
  • Geology
Information
Abstract
Self-organizing map projects highdimensional signal spaces on a two-dimensional displayable space, compressing information while preserving the most important topological relationships of the training patterns. These characteristics make self-organizing map a useful tool for multidimensional patterns visualization. In this work, a projection method of multidimensional data in two-dimensional space using growing self-organizing maps is proposed. With this projection technique, several traditional methods for visual analysis of Kohonen¿s self-organizing maps have been implemented for growing self-organizing maps. Different groups of multispectral data of images registered by Landsat-ETM+ and QuickBird satellites have been used to perform an exploratory visual analysis with this new graphical technique.
International
Si
Congress
Sensing and understanding our planet
960
Place
Piscataway, NJ, EEUU
Reviewers
Si
ISBN/ISSN
1-4244-1212-9
Start Date
End Date
From page
To page
Participants
  • Participante: Soledad Delgado Sanz
  • Autor: M.Estibaliz Martinez Izquierdo (UPM)
  • Autor: Agueda Arquero Hidalgo (UPM)
  • Autor: Consuelo Gonzalo Martin (UPM)
Research Group, Departaments and Institutes related
  • Creador: Grupo de Investigación: Informática Aplicada al Procesado de Señal e Imagen
  • Departamento: Arquitectura y Tecnología de Sistemas Informáticos
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