prikaz prve stranice dokumenta Segmentacija stomatoloških panoramskih rendgenskih snimaka
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undergraduate thesis
Segmentacija stomatoloških panoramskih rendgenskih snimaka
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:943867
Smoljan, Dorian
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Smoljan, D. (2021). Segmentacija stomatoloških panoramskih rendgenskih snimaka (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:943867

Smoljan, Dorian. "Segmentacija stomatoloških panoramskih rendgenskih snimaka." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:943867

Smoljan, Dorian. "Segmentacija stomatoloških panoramskih rendgenskih snimaka." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:943867

Smoljan, D. (2021). 'Segmentacija stomatoloških panoramskih rendgenskih snimaka', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 05 October 2024, https://urn.nsk.hr/urn:nbn:hr:168:943867

Smoljan D. Segmentacija stomatoloških panoramskih rendgenskih snimaka [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 October 05] Available at: https://urn.nsk.hr/urn:nbn:hr:168:943867

D. Smoljan, "Segmentacija stomatoloških panoramskih rendgenskih snimaka", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:943867

Metadata
TitleSegmentacija stomatoloških panoramskih rendgenskih snimaka
Title (english)Segmentation of Stomatologic Panoramic X-ray Images
AuthorDorian Smoljan
MentorMarko Subašić (mentor)
Committee memberMarko Subašić (predsjednik povjerenstva)
Committee memberDenis Milošević (član povjerenstva)
Committee memberKarlo Koščević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-07, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Cilj ovog rada bio je pronaći i testirati odgovarajuću arhitekturu za problem semantičke segmentacije kada je prisutan manji broj neoznačenih i veći broj označenih primjera. Predstavljena je cycleGAN arhitektura, te je testirana na konkretnom problemu semantičke segmentacije ortopanograma. Arhitektura je izabrana iz razloga što može iskorisiti i neoznačene slike kao pomoć pri treniranju. Dobiveni rezultati su pokazali da cycleGAN arhitektura uspješno rješava navedeni problem, no da ipak zaostaje u usporedbi s najnaprednijim diskriminativnim modelima.
Abstract (english)
The goal of this work was to find and test an adequate deep learning architecture applicable to the problem of semantic segmentation, in the case when we at our disposal have a limited number of labeled images, but a relatively high amount of unlabeled images. cycleGAN, a type of generative model was proposed as solution to the starting problem. It was chosen due to the fact that it can use unlabeled images as well as labeled to improve training performance. It was tested on the dataset of stomatologic X-ray images (orthopantomograms), and it was shown that while it successfully solves the given problem, it still falls behind most advanced discriminative models.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:943867
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 on2023-01-14 21:39:19