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Skin Cancer Detection from Smartphone Imagery using Convolutional Neural Network |
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| รหัสดีโอไอ | |
| Creator | Piyawat Nulek |
| Title | Skin Cancer Detection from Smartphone Imagery using Convolutional Neural Network |
| Contributor | Kwankamon Dittakan, Korawit Prutsachainimmit |
| Publisher | The Association of Council of IT Deans (CITT) |
| Publication Year | 2565 |
| Journal Title | Journal of Information Science and Technology |
| Journal Vol. | 12 |
| Journal No. | 2 |
| Page no. | 73-86 |
| Keyword | Skin Cancer Detection, Computer-Aided Diagnosis (CAD), Deep Learning |
| URL Website | https://tci-thaijo.org/index.php/JIST |
| Website title | Journal of Information Science and Technology |
| ISSN | 2651-1053 |
| Abstract | Skin cancer is an abnormal growth of human skin cells that develop on the skin, being exposed directly to ultraviolet radiation for an extended period. It is one of the most common health issues at a rapidly alarming rate around the world, with 160,000 medical records reported annually. Many records are in Europe, America, and New Zealand. In contrast, the least reported was in Thailand. Thus, the early detection of skin cancer to prevent the chance of developing skin cancer is the aim of this research. This paperpresentsa new methodology for detecting skin cancer from images using a Convolutional Neural Network (CNN) with Deep Learning. The PAD-UFES-20 datasets are used for training and testing the detection model. The image preprocessing techniques that help improve detection accuracy are also proposed. The results of our study show that the accuracy of the deep learning model in our experiment was 81.50%. |
