Color palette generation with Conditional Generative Adversarial Networks

diploma thesis

Sergei Burykin (Author), Aleksander Sadikov (Mentor)

Abstract

Creation of unique color palettes is a challenging task for designers all around the world. Every year it becomes increasingly difficult to create new color palettes. Color theory describes different algorithms for creation of color palettes, but these algorithms limit the possible color combinations. Designers all around the world are trying to find new ways to complete this task. We are trying to apply deep learning algorithms in order to create the color palettes which were never seen before. Using Generative Adversarial Networks (GAN) we can expand the amount of unique color palettes, since GANs are not limited by conventional algorithms.

Keywords

artificial intelligence;deep learning;generative adversarial networks;computer science;computer and information science;diploma;

Data

Language:	English
Year of publishing:	2021
Typology:	2.11 - Undergraduate Thesis
Organization:	UL FRI - Faculty of Computer and Information Science
Publisher:	[S. Burykin]
UDC:	004.8(043.2)
COBISS:	69404675
Views:	363
Downloads:	41
Average score:	0 (0 votes)
Metadata:

Other data

Secondary language:	Slovenian
Secondary title:	Ustvarjanje barvne palete s pogojnimi generativnimi nasprotniškimi mrežami
Secondary abstract:	Ustvarjanje edinstvenih barvnih palet je zahtevna naloga za oblikovalce po vsem svetu. Vsako leto je vse težje ustvarjati nove barvne palete. Teorija barv opisuje različne algoritme za ustvarjanje barvnih palet, vendar ti algoritmi omejujejo možne kombinacije barv. Oblikovalci po vsem svetu poskušajo najti nove načine za dokončanje te naloge. Poskušamo uporabiti algoritme globokega učenja, da bi ustvarili barvne palete, ki jih še nikoli nismo videli. Z uporabo Generativnih Nasprotniških Mrež (GAN) lahko razširimo količino unikatnih barvnih palet, saj GAN-i niso omejeni z običajnimi algoritmi.
Secondary keywords:	poglobljeno učenje;generativne nasprotniške mreže;računalništvo in informatika;visokošolski strokovni študij;diplomske naloge;Umetna inteligenca;Računalništvo;Univerzitetna in visokošolska dela;
Type (COBISS):	Bachelor thesis/paper
Study programme:	1000470
Thesis comment:	Univ. v Ljubljani, Fak. za računalništvo in informatiko
Pages:	31 str.
ID:	13103407