Detection of Melanoma Skin Cancer using Deep Learning

The skin cancer diagnosis system is a foretelling model that programmatically denotes the presence of melanoma cancer in the skin by assessing the dermoscopic images with the assistance of deep learning. It is caused due to unrepaired de-oxy ribonucleic acid[DNA] that triggers a mutation. These mutations cause the skin cells to proliferate rapidly and thereby forming malignant tumours. The primary purpose behind this analysis is to spot the presence of melanoma skin cancer at its preliminary stages by acquiring quick results with high accuracy. Our proposed model put forward a remedy for the trouble of exorbitant expenses behind the analysis is the least accuracy rate in identification and manual detection system which faces portability problem. In our model, dermatoscopic images are categorized to prognosticate skin cancer by making use of the multi-layered CNN approach. As an outcome, our model has produced an accuracy of 95.24% which is greater than the existing model by 1.66 percent.