Classification of melanoma skin cancer using convolutional neural network

One of the deadliest illnesses in the world is skin cancer. Accurately diagnosing skin lesions in their early stages might help clinicians make better decisions by raising the likelihood of a cure before cancer develops. However, due to the imbalance and scarcity of most skin illness photos utilized for training, obtaining automated skin cancer classification is challenging. The categorization of skin cancer has recently made extensive use of a variety of deep learning-based techniques to address the aforementioned problems and provide positive outcomes. The topic of skin cancer categorization is examined in this study. The suggested study uses CNN learning models to classify skin cancer to overcome this issue. Our research has led us to the conclusion that 82% accuracy is being used.