In terms of mortality, skin cancer is among the deadliest forms of cancer. A consistent automated method for skin lesion recognition is required for initial identification. This paper proposes an automated method for classifying skin cancers. The goal is to create a model that uses Deep Learning algorithms to diagnose skin cancer and classify it into several types. Various computer-aided solutions for the correct identification of melanoma cancer have been offered. A reliable CAD system, however, for exact melanoma identification is extremely difficult to develop. Either classic learning machines or deep learning approaches are used in existing systems. On the basis of this research, we suggest the use of an intelligent Region of Interest (ROI) system based on transference learning to recognize and distinguish between melanoma and other cancers Using an enhanced k-mean method, the images extract ROIs. The suggested ROI-based transference learning strategy exceeds previous classification systems that utilize entire images

Deep Learning, classification, Skin cancer, melanoma.