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master's thesis
Detekcija raka kože metodama strojnog učenja
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. urn:nbn:hr:168:552765
Skender, Josip
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

Cite this document

Skender, J. (2023). Detekcija raka kože metodama strojnog učenja (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:552765

Skender, Josip. "Detekcija raka kože metodama strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:552765

Skender, Josip. "Detekcija raka kože metodama strojnog učenja." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2023. https://urn.nsk.hr/urn:nbn:hr:168:552765

Skender, J. (2023). 'Detekcija raka kože metodama strojnog učenja', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 03 November 2024, https://urn.nsk.hr/urn:nbn:hr:168:552765

Skender J. Detekcija raka kože metodama strojnog učenja [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2023 [cited 2024 November 03] Available at: https://urn.nsk.hr/urn:nbn:hr:168:552765

J. Skender, "Detekcija raka kože metodama strojnog učenja", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2023. Available at: https://urn.nsk.hr/urn:nbn:hr:168:552765

Metadata
TitleDetekcija raka kože metodama strojnog učenja
Title (english)Skin cancer detection using machine learning
AuthorJosip Skender
MentorMislav Grgić (mentor)
Committee memberMislav Grgić (predsjednik povjerenstva)
Committee memberSonja Grgić (član povjerenstva)
Committee memberTomislav Kos (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2023-07-04, Croatia
Abstract
Ovaj diplomski rad istražuje primjenu strojnog učenja u detekciji raka kože. Prikazani su osnovni koncepti računalnog vida, strojnog učenja i dubokog učenja te je objašnjena primjena dubokog učenja u računalnom vidu. Također istražene su osnovne karakteristike raka kože, povijesni razvoj tehnologije detekcije tumora i izazovi s kojima se suočava. Rad također daje pregled dostupnih skupova podataka za detekciju tumora kože te predstavlja neke od dostupnih modela za ovu svrhu, uključujući VGGNet i ResNet. Metodologija rada obuhvaća pripremu HAM10000 skupa podataka, istraživačku analizu podataka, izgradnju i treniranje modela. Rezultati istraživanja prikazani su za različite modele korištene u radu te su uspoređeni međusobno i s modelima iz drugih aktualnih radova.
Abstract (english)
This thesis explores the application of machine learning in the detection of skin cancer. It presents the fundamental concepts of computer vision, machine learning, and deep learning, and explains the application of deep learning in computer vision. It also investigates the basic characteristics of skin cancer, the historical development of cancer detection technology, and the challenges faced. The thesis provides an overview of available datasets for skin cancer detection and introduces some of the available models for this purpose, including VGGNet and ResNet. This work includes the preparation of the HAM10000 dataset, data analysis, model building, and training. The research results are presented for different models used in the study and are compared among themselves and with models from other relevant works.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:552765
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
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Created on2023-10-11 10:26:39