[bachelor's] thesis
Abstract
In this thesis, we implement a neural style transfer model, which uses
so-called “meta networks” to train image transformation networks. A trained
image transformation network takes in two images - a content and a style image,
and generates a new image, combining the content from the first with the style
from the second image. We take an already existing model and train it on our
own style dataset, as well as reduce the size of the content dataset, in order to see
how to perform style transfer on a smaller amount of training data. Finally, we
create a website, which allows users to generate their own stylized images using
our trained models. At the end of the project we can say that meta networks have
proven to be very efficient for operations with smaller datasets and they produce
satisfactory results.
Keywords
artificial intelligence;neural networks;neural style transfer;meta networks;image transformation networks;content images;style images;computer and information science;diploma thesis;
Data
Language: |
English |
Year of publishing: |
2023 |
Typology: |
2.11 - Undergraduate Thesis |
Organization: |
UL FRI - Faculty of Computer and Information Science |
Publisher: |
[E. Kurbegović] |
UDC: |
004.8:7(043.2) |
COBISS: |
178678787
|
Views: |
26 |
Downloads: |
5 |
Average score: |
0 (0 votes) |
Metadata: |
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Other data
Secondary language: |
Slovenian |
Secondary title: |
Prenos sloga umetniških del z uporabo nevronskih omrežij |
Secondary abstract: |
V tem članku smo implementirali model za nevronski prenos sloga, ki
uporablja tako imenovana “meta omrežja” za ustvarjanje omrežij za preoblikovanje
slik. Usposobljeno omrežje za preoblikovanje slik sprejme dve sliki - vsebinsko in
stilsko sliko - ter ustvari novo sliko, pri čemer združi vsebino s prve slike s slogom
iz druge slike. Že obstoječi model učimo na lastni bazi podatkov stilskih slik
in zmanjšamo velikost baze podatkov vsebinskih slik, da bi videli, kako narediti
prenos sloga na manjši količini podatkov za učenje. Ustvarili smo spletno stran,
ki uporabnikom omogoča, da ustvarijo lastne stilizirane slike z uporabo naših usposobljenih
modelov. Ob zaključku lahko rečemo, da so se meta omrežja izkazala
za učinkovita z manjšimi nabori podatkov in dajejo zadovoljive rezultate. |
Secondary keywords: |
nevronski prenos sloga;meta mreže;mreže za preoblikovanje slik;vsebinske slike;slogovne slike;univerzitetni študij;diplomske naloge;Umetna inteligenca;Nevronske mreže (računalništvo);Slike;Računalništvo;Univerzitetna in visokošolska dela; |
Type (COBISS): |
Bachelor thesis/paper |
Study programme: |
1000468 |
Embargo end date (OpenAIRE): |
1970-01-01 |
Thesis comment: |
Univ. v Ljubljani, Fak. za računalništvo in informatiko |
Pages: |
58 str. |
ID: |
21708460 |