Monitoring changes in land use and land cover using deep learning methods
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URL
Journal Title
Journal ISSN
Volume Title
Insinööritieteiden korkeakoulu |
Master's thesis
Authors
Date
2023-12-11
Department
Major/Subject
Geoinformatics
Mcode
Degree programme
Master's Programme in Geoinformatics (GIS)
Language
en
Pages
67
Series
Description
Supervisor
Rönnholm, PetriThesis advisor
Zhu, LingliKeywords
land use, land cover, deep learning, aerial imagery, semantic segmentation