Skin Cancer Classification using Deep Learning Models

In recent years, researches proved that Melanoma is the deadliest form of skin cancer. In the early stages, it can be treated successfully with surgery alone and survival rates are high. A large number of methods for Melanoma classification has been proposed to deal with this problem, but although they did not find better ways to create the final solution. Thus, our aim is to go further and explore the classic models in order to handle the Melanoma classification problem based on modified VGG16 and modified InceptionV3. The conducted experiments revealed the effectiveness of our proposed method based on modified VGG16 with 73.33% of accuracy, when compared to other state-of-the-art methods on the same data sets, in terms of finding optimal and effective solutions and improving the objective function.