Skin Disease Detection using Machine Learning Framework’s CNN Algorithm

Abstract

The most frequent ailment in the world is a skin disease. Dermatologists must have high skill and accuracy when diagnosing skin diseases. Hence a computer-aided skin disease diagnosis model is offered as a more objective and dependable option. Many studies have been conducted to detect skin illnesses such as skin cancer and tumors. However, recognising the right disease by the following factors is complicated: low contrast between lesions and skin, visual similarity between the disease, and non-disease areas. This project will detect skin disease from a skin image. Further, it will analyze it using a filter to reduce noise or undesired objects. Then it will convert the image to grey to aid in processing and to extract valuable data using Machine Learning algorithms. This project can demonstrate emergency orientation and provide evidence for any form of skin illness.