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master's thesis
Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:255816
Car, Franko
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Car, F. (2021). Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:255816

Car, Franko. "Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:255816

Car, Franko. "Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:255816

Car, F. (2021). 'Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 July 2024, https://urn.nsk.hr/urn:nbn:hr:168:255816

Car F. Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 July 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:255816

F. Car, "Detekcija klizišta na LiDAR snimkama pomoću dubokog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:255816

Metadata
TitleDetekcija klizišta na LiDAR snimkama pomoću dubokog učenja
Title (english)Landslide Detection in LiDAR Images Using Deep Learning
AuthorFranko Car
MentorMarko Subašić (mentor)
Committee memberMarko Subašić (predsjednik povjerenstva)
Committee memberTomislav Petković (član povjerenstva)
Committee memberKrešimir Križanović (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-01, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu uvedeni su osnovni koncepti dubokog učenja i neuronskih mreža, modeli EfficientDet i YOLOv5 te je opisana njihova primjena na detekciju klizišta. Osnovni oblik podataka su LiDAR snimke koje predstavljaju visinski model terena. Uz detekciju na osnovnim visinskim modelima, oba navedena modela učena su i na deriviranim kartama osjenčanog terena. Na kraju, predstavljene su korištene metrike i konačni rezultati nad skupom podataka za testiranje.
Abstract (english)
This thesis introduces the foundations of deep learning and neural networks, EfficientDet and YOLOv5 deep learning models and their application in landslide detection. Basic data format are LiDAR images representing digital terrain models. Besides detecting landslides on the basic terrain models, both models were trained using the derived hillshaded maps as well. Finally, metrics used and final results on the test dataset are presented.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:255816
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-01-13 11:56:40