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DC Field | Value | Language |
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dc.contributor.author | Stefan Ćirković | - |
dc.contributor.author | Stanic, Nikola | - |
dc.date.accessioned | 2024-10-08T07:48:46Z | - |
dc.date.available | 2024-10-08T07:48:46Z | - |
dc.date.issued | 2024 | - |
dc.identifier.isbn | 9788677762766 | en_US |
dc.identifier.uri | https://scidar.kg.ac.rs/handle/123456789/21167 | - |
dc.description.abstract | Skin 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.iso | en | en_US |
dc.publisher | Faculty of Technical Sciences Čačak, University of Kragujevac | en_US |
dc.relation | MSTDI - 451-03-66/2024-03/200132 | en_US |
dc.relation.ispartof | 10th International Scientific Conference Technics, Informatics and Education - TIE 2024 | en_US |
dc.rights | CC0 1.0 Universal | * |
dc.rights.uri | http://creativecommons.org/publicdomain/zero/1.0/ | * |
dc.subject | skin cancer | en_US |
dc.subject | yolo | en_US |
dc.subject | neural network | en_US |
dc.title | Application of the YOLO algorithm for Medical Purposes in the Detection of Skin Cancer | en_US |
dc.type | conferenceObject | en_US |
dc.description.version | Published | en_US |
dc.identifier.doi | 10.46793/TIE24.083C | en_US |
dc.type.version | PublishedVersion | en_US |
Appears in Collections: | Faculty of Technical Sciences, Čačak |
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13 - I.11..pdf | 636.78 kB | Adobe PDF | View/Open |
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