Deep convolutional neural network for face skin diseases identification

The use of computer based technologies or Artificial intelligence in facial skin problems identification has evolved significantly over the years. In this paper, we propose an automated facial skin disease method using a pre-trained deep convolutional neural network (CNN). In the beginning, the images are regenerated using some pre-processing image techniques in order to augment the size of our database, collected from different sources and resized to fit the network. These images are then used for training and validation purposes. We will show that our model can successfully identify eight facial skin diseases, normal skin class and no-face class and with an accuracy of 88%.