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undergraduate thesis
Geometrijski pristup dubokom učenju
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:667170
Đomlija, Mislav
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Đomlija, M. (2023). Geometrijski pristup dubokom učenju (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:667170

Đomlija, Mislav. "Geometrijski pristup dubokom učenju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:667170

Đomlija, Mislav. "Geometrijski pristup dubokom učenju." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:667170

Đomlija, M. (2023). 'Geometrijski pristup dubokom učenju', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 04 October 2024, https://urn.nsk.hr/urn:nbn:hr:168:667170

Đomlija M. Geometrijski pristup dubokom učenju [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 October 04] Available at: https://urn.nsk.hr/urn:nbn:hr:168:667170

M. Đomlija, "Geometrijski pristup dubokom učenju", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:667170

Metadata
TitleGeometrijski pristup dubokom učenju
Title (english)Geometrical approach to deep learning
AuthorMislav Đomlija
MentorDario Bojanjac (mentor)
Committee memberDario Bojanjac (predsjednik povjerenstva)
Committee memberFilip Turčinović (član povjerenstva)
Committee memberDubravko Tomić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-06-29, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
U ovom radu smo na jasan način prezentirali osnove Riemannove geometrije i njenu primjenu na standardnu arhitekturu neuronske mreže. Izveli smo način za računanje nivo hiperploha u podatkovnoj domeni i to primjenili na jednostavnu neuronsku mrežu koja obavlja logističku regresiju nad trodimenzionalnim točkama
Abstract (english)
In this paper, we presented the basics of Riemannian geometry and its application on standard neural network architecture. We developed a framework to calculate level hyperplanes in the data domain and we applied that to simple neural network, trained to do logistic regression on 3D points.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:667170
Study programmeTitle: Computing
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-07-13 10:02:36