Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13087/3497
Title: COMPARISON OF DEEP LEARNING WITH MACHINE LEARNING ON SKIN SEGMENTATION
Authors: Fidan, Mehmet
Kaya, Utku
Keywords: 
Issue Date: 2021
Abstract: In this study, a skin segmentation study is investigated with deep learning methods. The skin segmentation problem is chosen as a case study. The main reason for this is that there are numerous studies on this subject and the abundance of available data sets. In addition, images containing skin pixels contain multiple attributes. That's why human images are very suitable for comparative studies on machine learning and deep learning. In the first stage of this study, skin segmentation will be done by using RGB space, which contains deep information as an attribute in machine learning. At the same time, to show the success of the deep learning algorithm, the effect of deep learning will be tested by converting images to grayscale, and success differences will be given
URI: https://doi.org/10.20290/estubtdb.1011591
https://search.trdizin.gov.tr/yayin/detay/519002
https://hdl.handle.net/20.500.13087/3497
ISSN: 2667-419X
Appears in Collections:TR-Dizin İndeksli Yayınlar Koleksiyonu
Ulaştırma Meslek Yüksekokulu Yayın Koleksiyonu

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