Open Access
Skin Cancer Classification into Three Classes
Cihan Akyel1*
1Gazi University, Ankara, Turkey
* Corresponding author: cihan.akyel1@gazi.edu.tr

Presented at the 6th International Symposium on Innovative Approaches in Smart Technologies (ISAS-WINTER-2022), Online, Turkey, Dec 08, 2022

SETSCI Conference Proceedings, 2022, 14, Page (s): 38-40 , https://doi.org/10.36287/setsci.5.2.008

Published Date: 22 December 2022    | 2660     15

Abstract

The incidence of skin cancer is increasing. Early detection of cases of skin cancer is vital for treatment. Recently, computerized methods have been widely used in cancer diagnosis. These methods have important advantages such as no human error, short diagnosis time, and low cost. Melanoma is most dangerous type of skin cancer. Basal cell carcinoma is type with high cancer potential. Properly classified images can help doctors predict the type of skin cancer.  This study aims to classify into three classes, including the normal type.

Keywords - Deep learning, skin cancer, image classification, ResNet, LinkNet

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