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Title:Kategorizacija in detekcija sprememb v radarskih slikah sar z uporabo algoritma globokega učenja
Authors:ID Obal, Aleš (Author)
ID Gleich, Dušan (Mentor) More about this mentor... New window
Files:.pdf MAG_Obal_Ales_2018.pdf (4,20 MB)
MD5: 3EF5CCE587A4E906C319DE12F96F0D5C
PID: 20.500.12556/dkum/cedd8cab-4cbb-45da-b87d-84f6122cbae4
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V magistrskem delu je opisan postopek kategorizacije in detekcije sprememb v radarskih slikah SAR z uporabo konvolucijske nevronske mreže, tako imenovane »Deep Learning«. V ta namen je bil izdelan program v Matlab programskem okolju, ki je sposoben izrezati SAR radarsko sliko na poljubne manjše dele, ustvariti konvolucijsko nevronsko mrežo, jo naučiti ter uporabiti pri klasifikaciji in detekciji predelov površja na Zemlji. Programu je dodana tudi opcija uporabe grafično procesne enote »GPU« za pohitritev učenja konvolucijskih nevronskih mrež.
Keywords:SAR, kategorizacija slik, detekcija sprememb v sliki, globoke nevronske mreže, paralelno procesiranje
Place of publishing:[Maribor
Publisher:A. Obal
Year of publishing:2018
PID:20.500.12556/DKUM-69337 New window
UDC:004.032.26:550.837.7(043.2)
COBISS.SI-ID:21209110 New window
NUK URN:URN:SI:UM:DK:PQIOLGLL
Publication date in DKUM:09.02.2018
Views:1739
Downloads:213
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:08.01.2018

Secondary language

Language:English
Title:Categorization and change detection using synthetic aperture radar data with deep learning algorithm
Abstract:The master's thesis describes the process of categorization and detection of changes in SAR radar images using a convolutional neural network, the so-called "Deep Learning." A program was developed In the Matlab program environment for this purpose. The program is capable of cutting the SAR radar image into smaller thumbnails, creating convolution neural network for learning and recognition of Earth's surface parts and changes on it. The program also contains an option to use the graphics processing unit »GPU« for speeding up the learning process of the convolutional neural network.
Keywords:SAR, image categorization, change detection in image, deep neural networks, parallel processing


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