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Určení výskytu sněhových lavin z družicových dat pořízených radarem se syntetickou aperturou (SAR) / Detection of snow avalanche debris from satellite synthetic aperture radar (SAR) data

DETECTION OF SNOW AVALANCHE DEBRIS FROM SATELLITE SYNTHETIC APERTURE RADAR (SAR) DATA Abstract This thesis engages with detection of snow avalanche debris at radar images taken with synthetic aperture radar on Sentinel-1 satellite. The aim is to find method for recognizing places at image where is the snow avalanche debris. A method is based on neural net principle, specifically on using pre-trained model of neural net VGG-19. According to results of neural net, training images are splitted into two cathegories: there is an avalanche and there is not. It is called binary classification. The result is statistical evaluation of success rate compared with other traditional methods. keywords: snow avalanche, Sentinel-1, neural net, VGG-19

Identiferoai:union.ndltd.org:nusl.cz/oai:invenio.nusl.cz:405425
Date January 2019
CreatorsKlímová, Tereza
ContributorsKolář, Jan, Brodský, Lukáš
Source SetsCzech ETDs
LanguageCzech
Detected LanguageEnglish
Typeinfo:eu-repo/semantics/masterThesis
Rightsinfo:eu-repo/semantics/restrictedAccess

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