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Dokumenttyp:
Misc 
Autor(en):
Liebel, Lukas 
Titel:
Deep Convolutional Neural Networks for Semantic Segmentation of Multispectral Sentinel-2 Satellite Imagery: An Open Data Approach to Large-Scale Land Use and Land Cover Classification 
Abstract:
In this thesis, the applicability of deep convolutional neural network s (CNNs) for large-scale land use and land cover (LULC) classification is evaluated. A state-of-the-art image recognition CNN architecture was adapted and re-trained from scratch using a novel dataset. LULC classification is a common task in remote sensing. Large-scale LULC maps are mainly used for scientific analyses and serve as a basis for decision making by governments and non-governmental organizations (NGOs). Several pr...    »
 
Stichworte:
lulc 
Monat:
Jul 
Jahr:
2017 
TUM-Einrichtung:
Lehrstuhl für Methodik der Fernerkundung