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DeepSkin: Robust Skin Cancer Classification Using Convolutional Neural Network Algorithm
ISSN: ISSN - N268
Publisher: author
DeepSkin: Robust Skin Cancer Classification Using Convolutional Neural Network Algorithm
Indexed in
Technology and Engineering
ARTICLE-FACTOR
1.3
Article Basics Score: 2
Article Transparency Score: 3
Article Operation Score: 3
Article Articles Score: 3
Article Accessibility Score: 3
SUBMIT PAPER ASK QUESTION
International Category Code (ICC):
ICC-1802
Publisher: International Journal Of Informatics And Computation (ijic..
eISSN
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ISSN - N268
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Abstract
Classification of skin cancer is a growing research topic with significant challenges in image processing. Learning algorithms for classifying a kind of skin cancer have been presented in recent articles to accelerate the diagnosis process with a rapid and accurate diagnosis. However, effective detection of skin cancer requires extensive graphical data. Inspired by deeplearning successful results in computer vision, A Convolutional Neural Network (CNN) is proposed in this study to build a skin cancer classification model. We conduct this experiment by collecting massive skin cancer datasets, conducting pre-processing, training models, and evaluating the performance. Based on the experiment result, the benign and malignant classification model can obtain a good accuracy with a slight loss. Therefore, the results obtained reached an accuracy of 54%.
