Skin Disease Classification Using Deep Neural Networks With Resnet

Abstract

Skin diseases have a serious impact on people's life and health. The most prevalent type of illness that affect people of all ages is skin disorders. A significant burden is attached to skin conditions, which are among the most prevalent health issues in the globe. The psychological, social, and economic effects of skin diseases on patients, their families, and society as a whole are all included in the multifaceted concept of the burden of skin disease. Deep learning models are efficient in learning the features that assist in understanding complex patterns precisely. The ResNet CNN architecture is used over the dataset randomly collected from Google for the identification of ten kinds of skin diseases. The highest accuracy obtained for the model is 99.87% and 98.84% for training and testing sets respectively.