Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/21167
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dc.contributor.authorStefan Ćirković-
dc.contributor.authorStanic, Nikola-
dc.date.accessioned2024-10-08T07:48:46Z-
dc.date.available2024-10-08T07:48:46Z-
dc.date.issued2024-
dc.identifier.isbn9788677762766en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/21167-
dc.description.abstractSkin cancer is one of the most common forms of cancer worldwide. Exposure to ultraviolet (UV) radiation increases the risk of its development. Early preventive examinations and early detection of suspicious skin changes are key factors for successful treatment. Due to the rapid development of AI technologies, neural networks have found application in various fields, including medicine. Neural networks can be used to create various applications, which would facilitate self-examination for patients and alert them to potential problems. This method would further save time and reduce healthcare costs. The paper presents the application of a neural network using the YOLO (You Only Look Once) algorithm on a dataset of mole images with the aim of identifying and classifying moles, which facilitates early intervention and improves treatment outcomes.en_US
dc.language.isoenen_US
dc.publisherFaculty of Technical Sciences Čačak, University of Kragujevacen_US
dc.relationMSTDI - 451-03-66/2024-03/200132en_US
dc.relation.ispartof10th International Scientific Conference Technics, Informatics and Education - TIE 2024en_US
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.subjectskin canceren_US
dc.subjectyoloen_US
dc.subjectneural networken_US
dc.titleApplication of the YOLO algorithm for Medical Purposes in the Detection of Skin Canceren_US
dc.typeconferenceObjecten_US
dc.description.versionPublisheden_US
dc.identifier.doi10.46793/TIE24.083Cen_US
dc.type.versionPublishedVersionen_US
Appears in Collections:Faculty of Technical Sciences, Čačak

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