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Title:Prenos stila slike s pomočjo prenosnega učenja in nevronskih mrež : magistrsko delo
Authors:ID Colakovic, Ivona (Author)
ID Karakatič, Sašo (Mentor) More about this mentor... New window
Files:.pdf MAG_Colakovic_Ivona_2021.pdf (3,40 MB)
MD5: 5F35182C7DD47AA88F0C1CB67A3F04FE
PID: 20.500.12556/dkum/90a9c4d9-6576-4218-94fc-10dc222b59d7
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:Hitro razvijajoče področje umetne inteligence se v zadnjih letih integrira v različna področja in tako postaja neizogiben del številnih človeških dejavnosti. Umetna inteligenca je pokazala, da se lahko integrira tudi v področje umetnosti in ustvarja nova umetniška dela a podlagi kopiranja stilov grafičnih del priznanih avtorjev. Nevronske mreže, ki posnamejo delovanje človeških možganov, dodatno pomagajo pri tem postopku, saj omogočajo razpoznavo vzorcev v stilih grafičnih del. V magistrskem delu se osredotočimo na raziskovanje tehnike prenosa stila grafičnih del iz enega na drugo grafično delo s pomočjo nevornskih mrež. V ta namen opišemo sestavne dele nevronskih mrež, podrobneje razložimo konvolucijske nevronske mreže in predstavimo pojem prenosnega učenja. Z namenom boljšeg razumevanja področja prenosa stila ilustracij pregledamo obstoječe raziskave ter opišemo delovanje algoritma za prenos stila. V okviru magistrskega dela prikažemo implementacijo in rezultate eksperimenta skozi katerega smo ugotovili, da pristop prenosa stila lahko uspešno prenaša stil iz ilustracij na fotografije kakor tudi iz ilustracij na druge ilustracije.
Keywords:prenos stila, konvolucijske nevronske mreže, prenosno učenje
Place of publishing:Maribor
Place of performance:Maribor
Publisher:[I. Čolaković]
Year of publishing:2021
Number of pages:XI, 56 str.
PID:20.500.12556/DKUM-80024 New window
UDC:004.85:004.93(043.2)
COBISS.SI-ID:82420227 New window
Publication date in DKUM:18.10.2021
Views:1170
Downloads:129
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
:
COLAKOVIC, Ivona, 2021, Prenos stila slike s pomočjo prenosnega učenja in nevronskih mrež : magistrsko delo [online]. Master’s thesis. Maribor : I. Čolaković. [Accessed 22 March 2025]. Retrieved from: https://dk.um.si/IzpisGradiva.php?lang=eng&id=80024
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:26.08.2021

Secondary language

Language:English
Title:Image style transfer using transfer learning and neural networks
Abstract:Artificial Intelligence, a rapidly evolving field, has became an inevitable part of many human activities due to integration into different field. Artificial Intelligence has shown it can be integrated even into art by creating new works of art based on copying works of renowned authors. Neural networks which imitate the functioning of human brain further help in this field as they are able to recognize patterns in images. In Master’s thesis we focus on researching image style transfer techniques. For this purpose we describe neural networks components, explain convolutional neural networks and introduce the concept of transfer learning. In order to better understand the field of style transfer, we review existing research and describe the style transfer algorithm. In Master’s thesis we show the implementation and results of experiment that helped us conclude that approach of style transfer can be used to successfully transfer style from image to the photography or ilustrations.
Keywords:style transfer, convolutional neural networks, transfer learning


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