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Title:Ocenjevanje vlažnosti tal z uporabo radarskih slik in globokega učenja : magistrsko delo
Authors:ID Peterkovič, Tomaž (Author)
ID Gleich, Dušan (Mentor) More about this mentor... New window
Files:.pdf MAG_Peterkovic_Tomaz_2021.pdf (8,61 MB)
MD5: CD71459C5E3B317E5257DEEE9CB41D85
PID: 20.500.12556/dkum/6c1e87b2-d452-493f-a480-a1e4c1db7ee2
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Magistrsko delo temelji na obdelavi satelitskih slik in uporabi globokih konvolucijskih nevronskih mrež. V vsebini zaključnega dela je opisano raziskovalno delo s področja uporabe polarimetričnega SAR-a. Namen dela je načrtovanje in izdelovanje sistema, ki bi lahko bil sposoben obdelati satelitsko sliko tako, da se iz nje lahko določi vlažnost tal. Za ocenjevanje le-te so bile uporabljene globoke konvolucijske nevronske mreže, ki so se izkazale za zelo uporabne. V postopku izdelave so bili uporabljeni programi za obdelovanje atmosferskih slik s pomočjo polarimetrije, kot so PolSARpro in SNAP. Za nadaljnjo obdelavo slik in načrtovanje globoke konvolucijske nevronske mreže se je uporabljal programski jezik Python v okolju Visual Studio.
Keywords:Daljinsko zaznavanje, nevronske mreže, ocenjevanje vlažnosti tal, polarimetrija, PolSARpro, Python
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[T. Peterkovič]
Year of publishing:2021
Number of pages:X, 84 str.
PID:20.500.12556/DKUM-80252 New window
UDC:520.85:681.542.4(043.2)
COBISS.SI-ID:83194371 New window
Publication date in DKUM:18.10.2021
Views:956
Downloads:132
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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Licences

License:CC BY-SA 4.0, Creative Commons Attribution-ShareAlike 4.0 International
Link:http://creativecommons.org/licenses/by-sa/4.0/
Description:This Creative Commons license is very similar to the regular Attribution license, but requires the release of all derivative works under this same license.
Licensing start date:03.09.2021

Secondary language

Language:English
Title:Evaluation of soil humidity using radar images and deep learning
Abstract:The master's thesis is based on the processing of satellite images and the use of deep convolutional neural networks. In the content there is described research work in the field of polarimetric SAR. The purpose of the work is to design and manufacture a system, that could be able to process a satellite image so that soil moisture can be determined from it. To evaluate this, we used deep convolutional neural networks, which we believe could prove very useful. In the developing process, we used programs for processing atmospheric images using polarimetry. such as PolSARpro and SNAP. The Python programming language in the Visual Studio environment was used to further process the images and design the deep convolutional neural network.
Keywords:Remote sensing, neural networks, evaluation of soil humidity, polarimetry, PolSARpro, Python


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