Monkay Pox Skin Disease Detection Using Deep Learning

Abstract

Human skin illnesses are widespread; millions of individuals are afflicted with different types of skin conditions. These illnesses often include unstated risks that increase the chance of developing skin cancer in addition to psychological sadness and low self-esteem. Because skin disease photos lack visual resolution, medical professionals and advanced equipment are required for the identification of these conditions. The suggested system makes use of preexisting models like Alex Net, ResNet, and InceptionV3 as well as deep learning methods like CNN architecture. A dataset of seven distinct illnesses has been collected in order to classify skin disorders. These include ailments such as nevus, seborrheic keratosis, melanoma, and so on. Images of burns and cuts, which were categorized as skin diseases by the majority of the systems in place, were included to the collection. Human labor is no longer required for tasks like manual feature extraction and data reconstruction for classification thanks to the use of deep learning algorithms.