Classification of Vitiligo using CNN Autoencoder

Precise recognition of skin ailment is a time-consuming procedure even for Professionals. With the invention of deep learning and medical image processing, the identification of skin disease is possible in a time-efficient manner and accurately. Autoencoder is the generative algorithm but in the proposed work it is used as a generator and as well as a classifier. In this work, a Convolutional (CNN) autoencoder was used to classify the skin disease Vitiligo. In this work encoding and decoding layers were used but in the last layer in place of reproducing the original image, the classification layer was used to classify the image. The proposed work gave training accuracy of 87.71 % whereas validation accuracy was 90.16%.