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undergraduate thesis
Semantička segmentacija harmoničkim gusto povezanim modelima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. urn:nbn:hr:168:033039
Delić, Anja
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Delić, A. (2021). Semantička segmentacija harmoničkim gusto povezanim modelima (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:033039

Delić, Anja. "Semantička segmentacija harmoničkim gusto povezanim modelima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:033039

Delić, Anja. "Semantička segmentacija harmoničkim gusto povezanim modelima." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2021. https://urn.nsk.hr/urn:nbn:hr:168:033039

Delić, A. (2021). 'Semantička segmentacija harmoničkim gusto povezanim modelima', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 25 August 2024, https://urn.nsk.hr/urn:nbn:hr:168:033039

Delić A. Semantička segmentacija harmoničkim gusto povezanim modelima [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2021 [cited 2024 August 25] Available at: https://urn.nsk.hr/urn:nbn:hr:168:033039

A. Delić, "Semantička segmentacija harmoničkim gusto povezanim modelima", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2021. Available at: https://urn.nsk.hr/urn:nbn:hr:168:033039

Metadata
TitleSemantička segmentacija harmoničkim gusto povezanim modelima
Title (english)Semantic segmentation with harmonic densely connected models
AuthorAnja Delić
MentorSiniša Šegvić (mentor)
Committee memberSiniša Šegvić (predsjednik povjerenstva)
Committee memberPetra Bevandić (član povjerenstva)
Committee memberJosip Šarić (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2021-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Jedan od mnogih zanimljivih zadataka računalnog vida je semantička segmentacija. Modeli s gusto povezanim konvolucijskim slojevima postižu vrlo dobre rezultate, a u posljednje vrijeme pojavila su se poboljšanja koja pažljivim povezivanjem konvolucijskih slojeva nastoje smanjiti broj memorijskih zahtjevnih operacija tijekom učenja i testiranja bez smanjenja točnosti modela. U ovom radu predstavljene su harmoničke gusto povezane konvolucijske mreže te je provedeno učenje i evaluacija modela FCHarDNet70, jedne konkretne implementacije harmoničkog gusto povezanog modela. Rezultati su prikazani i objašnjeni na kraju rada. Dodatno, ukratko su opisane osnove dubokog učenja i konvolucijskih mreža. Opisan je i postupak učenja, korišteni skupovi podataka, detalji programske implementacije i korištene biblioteke.
Abstract (english)
One of the many interesting tasks of computer vision is semantic segmentation. Models with densely connected convolutional layers achieve very good results, and recently there have been improvements that, by carefully connecting convolutional layers, seek to reduce the number of memory-demanding operations during learning and testing without reducing model accuracy. In this paper, harmonic densely connected convolutional networks are presented and the learning and evaluation of the FCHarDNet70 model, a specific implementation of a harmonic densely connected model, is performed. The results are presented and explained at the end of the paper. Additionally, the basics of deep learning and convolutional networks are briefly described. The learning process, used data sets, details of program implementation and used libraries are also described.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:033039
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 20:17:27