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Title:Interaktivno modeliranje terena z nevronskimi mrežami
Authors:ID Novak, Robi (Author)
ID Strnad, Damjan (Mentor) More about this mentor... New window
ID Kohek, Štefan (Comentor)
Files:.pdf UN_Novak_Robi_2018.pdf (1,29 MB)
MD5: E56687EF0991BA8CDE86CEFCDCFA2AAE
PID: 20.500.12556/dkum/758d088d-bcff-483b-a50a-21ae4b323abe
 
.zip UN_Novak_Robi_2018.zip (2,90 MB)
MD5: 6DCAF9B51E61A18DA5FBB2F318ADA2D4
PID: 20.500.12556/dkum/3eda98d0-e408-48f4-833a-c5ffb1763e23
 
Language:Slovenian
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FERI - Faculty of Electrical Engineering and Computer Science
Abstract:V diplomskem delu smo implementirali generiranje terena z globokim učenjem. V ta namen smo uporabili pogojno generativno nasprotovalno mrežo (angl. conditional generative adversarial network) za tvorbo slike terena iz skic, kjer so označeni poteki vrhov in dolin. Naučena mreža omogoča interaktivno modeliranje terena, tako da uporabnik dopolnjuje skico, mreža pa sliko terena sproti prilagaja uporabnikovemu vnosu. Implementirali smo tudi prostorsko vizualizacijo generiranega terena z uporabo programskega vmesnika OpenGL.
Keywords:generiranje terena, modeliranje terena, nevronske mreže
Place of publishing:[Maribor
Publisher:R. Novak
Year of publishing:2018
PID:20.500.12556/DKUM-71906 New window
UDC:004.032.26(043.2)
COBISS.SI-ID:21859606 New window
NUK URN:URN:SI:UM:DK:OQOSR8KP
Publication date in DKUM:14.11.2018
Views:1622
Downloads:254
Metadata:XML DC-XML DC-RDF
Categories:KTFMB - FERI
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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:03.09.2018

Secondary language

Language:English
Title:Interactive terrain modeling with neural networks
Abstract:In our work, we have implemented terrain generation using deep learning. We have applied conditional generative adversarial networks to terrain synthesis from ridge and valley sketches. A trained network allows for interactive terrain modeling where the user completes the sketch, while the network adjusts the terrain to the user's input. We also implemented a spatial visualization of generated terrain using OpenGL.
Keywords:terrain generation, terrain modeling, neural networks


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