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Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures

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Bibliographic Details
Published in:Journal of Intelligent Systems : Theory and Applications
Format: Online Article RSS Article
Published: 2026
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container_title Journal of Intelligent Systems : Theory and Applications
description
discipline_display Engineering & Technology
discipline_facet Engineering & Technology
format Online Article
RSS Article
genre Journal Article
id rss_article:43062
institution FRELIP
journal_source_facet Journal of Intelligent Systems : Theory and Applications
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
— — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
sub_discipline_display Computer Science & IT
sub_discipline_facet Computer Science & IT
subject_display — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
— — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
subject_facet — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
title Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_auth Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_full Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_fullStr Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_full_unstemmed Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_short Automated Skin Lesion Segmentation in Medical Images Using U-Net Architectures
title_sort automated skin lesion segmentation in medical images using u-net architectures
topic — — — — — — Artificial Intelligence
Computer Science & IT
Engineering & Technology
url https://dergipark.org.tr/en/pub/jista/article/1671052%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20%20