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|Title:||COMPARISON OF DEEP LEARNING WITH MACHINE LEARNING ON SKIN SEGMENTATION||Authors:||Fidan, Mehmet
|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
|Appears in Collections:||TR-Dizin İndeksli Yayınlar Koleksiyonu|
Ulaştırma Meslek Yüksekokulu Yayın Koleksiyonu
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