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Journals / Turkish Journal of Science and Technology / 2021 / Volume: 16 Issue: 2

Classification of Skin Cancer Images with Convolutional Neural Network Architectures

Muhammed Yıldırım(FIRAT ÜNİVERSİTESİ)0000-0003-1866-4721
Ahmet Çınar(FIRAT ÜNİVERSİTESİ)0000-0001-5528-2226
Pages
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Publication Date
2021-09-15
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

This rate is an important value for early diagnosis and treatment of the disease.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The skin, in which our body is completely covered, both provides the heat balance of our body and protects our body against external factors.
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Key Findings & Data:With early diagnosis, patients can be cured earlier and mortality rates can be reduced.
💡
Conclusion & Impact:This rate is an important value for early diagnosis and treatment of the disease.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:CNN · Classification · Deep Learning

Abstract

The skin, in which our body is completely covered, both provides the heat balance of our body and protects our body against external factors. Skin cancers, which occur as a result of the uncontrolled proliferation of cells on the skin surface, are one of the most common types of cancer in the world. Early detection of skin cancers means early treatment of the disease. With early diagnosis, patients can be cured earlier and mortality rates can be reduced. The hardest part of skin cancer diagnosis is that skin lesions are very similar to each other. Therefore, it is of great importance that skin cancer can be diagnosed and classified as benign or malignant tumor. In this study, Convolutional Neural Network networks are used to determine whether skin cancer is benign or malignant. Separate results are obtained with Alexnet, Resnet50, Densenet201 and Googlenet. Then the performance rates of the models used have been compared. The highest accuracy rate is achieved with the Resnet50 model with 83.49%. This rate is an important value for early diagnosis and treatment of the disease.

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Cite This Article

Yıldırım, M., Çınar, A. (2021). Classification of Skin Cancer Images with Convolutional Neural Network Architectures. Turkish Journal of Science and Technology, Volume: 16 Issue: 2. https://ajindex.com/articles/1557833

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