Real Time-based Skin Cancer Detection System using Convolutional Neural Network and YOLO

Skin cancer arises by developing abnormal cells that invade or spread to other body parts. Nowadays, when a doctor examining someone’s skin to make sure the patient has skin cancer or not, the patient still has to go through a process where after result carried out by the doctor, the patient still has to wait for the results to know the patient has skin cancer or not. No. In thisproject, the author has designed a skin cancer detection system in real-time to increase the efficiency of the skin cancer detection process for patients without waiting for data from the hospital lab. We use the Convolution Neural Network (CNN) to process skin images and for data grouping and YOLO for the system in real-time. The goal is to design a skin cancer detection system that makes it easier and increases the efficiency of doctors in analysing the results of skin cancer. The model shows the absolute accuracy is 96 per cent, and the real-time using YOLOV3, the accuracy is 80%.