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undergraduate thesis
Analiza stomatoloških rendgenskih slika pomoću dubokog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. urn:nbn:hr:168:568791
Sikora, Toma
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Sikora, T. (2020). Analiza stomatoloških rendgenskih slika pomoću dubokog učenja (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:568791

Sikora, Toma. "Analiza stomatoloških rendgenskih slika pomoću dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:568791

Sikora, Toma. "Analiza stomatoloških rendgenskih slika pomoću dubokog učenja." Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2020. https://urn.nsk.hr/urn:nbn:hr:168:568791

Sikora, T. (2020). 'Analiza stomatoloških rendgenskih slika pomoću dubokog učenja', Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 05 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:568791

Sikora T. Analiza stomatoloških rendgenskih slika pomoću dubokog učenja [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2020 [cited 2024 November 05] Available at: https://urn.nsk.hr/urn:nbn:hr:168:568791

T. Sikora, "Analiza stomatoloških rendgenskih slika pomoću dubokog učenja", Undergraduate thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2020. Available at: https://urn.nsk.hr/urn:nbn:hr:168:568791

Metadata
TitleAnaliza stomatoloških rendgenskih slika pomoću dubokog učenja
Title (english)Analysis of Dental X-ray Images Using Deep Learning Methods
AuthorToma Sikora
MentorMarko Subašić (mentor)
Committee memberMarko Subašić (predsjednik povjerenstva)
Committee memberKarlo Koščević (član povjerenstva)
Committee memberDenis Milošević (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2020-07-09, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Modeli dubokog učenja danas se primjenjuju na većini područja čovjekova života. Osim raznih vrsta asistencije u svakodnevnom životu, ispituje se i njihova vrijednost kao profesionalnih alata. Jedna od struka na koje primjena dubokog učenja može imati pozitivan utjecaj je dentalna forenzika. Ovaj rad bavi se analizom stomatoloških rendgenskih slika uz pomoć metoda dubokog učenja. U sklopu ovog rada, ispituje se primjena konvolucijskih i predtrenirannih neuronskih mreža na probleme klasifikacije spola i regresije dobi osobe kojoj pripada slika. Također, i¬spituje se i utjecaj metoda manipulacije podacima kao što su stratifikacija i augmentacija slika na performanse mreže.
Abstract (english)
Nowadays, deep learning methods are being used in nearly every aspect of human life. Besides various sorts of everyday assistance, their use as a professional tool is the subject of many studies. One of the professions which could potentially benefit from their use is dental forensics. This thesis focuses on the analysis of dental X-ray images using deep learning methods. It studies the application of convolutional and pretrained neural networks to solve the problem of gender classification and age regression based on the dental X-ray image. Furthermore, it studies the effect several data manipulation methods such as data stratification and data augmentation have on the results.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:568791
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 on2023-01-13 16:04:23