Acne Skin Disease Detection Using Convolutional Neural Network Model

Abstract

Skin issues have been a colossal concern among ladies as well as men. This paper proposes a strategy for recognizing and classifying skin breaks out on the skin using CNN pre-trained model VGG19. Now days, these pretrained models have accomplished close or indeed way better execution than human creatures based on clinical pictures. A dataset of pictures of skin break out on the skin have been collected and pre-processed to get guarantee that the skin breakout is obvious or not. A CNN VGG19 model shows that the points built and trained on the datasets employ an appropriate optimization calculation. The model's execution is assessed on a testing set and the hyperparameters that we got from it and the engineering of the demonstration are fine-tuned to move forward with better execution. This research paper presents the image acquisition methods, datasets, deep learning architectures, and frameworks used in skin disease diagnosis. The proposed strategy appears promising comes about for identifying and classifying skin breaks out on the skin and has potential applications in dermatology clinics and skin care item advancement.