RT Dissertation/Thesis
T1 Techniques for the extraction of spatial and spectral information in the supervised classification of hyperspectral imagery for land-cover applications
A1 Acción Montes, Álvaro
K1 Hyperspectral
K1 image processing
K1 classification
K1 segmentation
K1 SLIC
K1 CNN
K1 data augmentation
AB The objective of this PhD thesis is the development of spatialspectralinformation extraction techniques for supervisedclassification tasks, both by means of classical models andthose based on deep learning, to be used in the classificationof land use or land cover (LULC) multi- and hyper-spectralimages obtained by remote sensing. The main goal is theefficient application of these techniques, so that they are ableto obtain satisfactory classification results with a low use ofcomputational resources and low execution time.
YR 2023
FD 2023
LK http://hdl.handle.net/10347/30758
UL http://hdl.handle.net/10347/30758
LA eng
DS Minerva
RD 24 abr 2026