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

Autor: Acción Montes, Álvaro
Přispěvatelé: Blanco Heras, Dora, Argüello Pedreira, Francisco Santiago, Universidade de Santiago de Compostela. Escola de Doutoramento Internacional (EDIUS), Universidade de Santiago de Compostela. Programa de Doutoramento en Investigación en Tecnoloxías da Información
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Popis: 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.
Databáze: OpenAIRE