Techniques for the extraction of spatial and spectral information in the supervised classification of hyperspectral imagery for land-cover applications

• Autores: Álvaro Acción
• Directores de la Tesis: Dora Blanco Heras (dir. tes.), Francisco Argüello Pedreira (dir. tes.)
• Lectura: En la Universidade de Santiago de Compostela ( España ) en 2023
• Idioma: inglés
• Número de páginas: 133
• Tribunal Calificador de la Tesis: Raúl Celestino Guerra Fernández (presid.), Natalia Seoane Iglesias (secret.), Javier Muro Martín (voc.)
• Programa de doctorado: Programa de Doctorado en Investigación en Tecnologías de la Información por la Universidad de A Coruña y la Universidad de Santiago de Compostela
• Materias:
  • Ciencias tecnológicas
    • Tecnología de los ordenadores
      • Arquitectura de ordenadores
• Enlaces
  • Tesis en acceso abierto en: MINERVA
• Resumen

  • The objective of this PhD thesis is the development of spatialspectral information extraction techniques for supervised classification tasks, both by means of classical models and those based on deep learning, to be used in the classification of land use or land cover (LULC) multi- and hyper-spectral images obtained by remote sensing. The main goal is the efficient application of these techniques, so that they are able to obtain satisfactory classification results with a low use of computational resources and low execution time.