Rating wrinkled skin using deep learning

딥러닝 기반 주름 평가

The paper proposes a new deep network-based model that rates periorbital wrinkles in order to alleviate the shortcomings of the evaluation by human experts as well as to facilitate the automation. Periorbital wrinkles still need to be classified by human experts. Furthermore, the classification results from experts are different from each other in many cases due to the inter-interpreter variability and the absence of quantification criteria. Unlike existing classification methods which classify original images, the proposed model consists of a cascade of two deep networks: U-Net for the enhancement of wrinkles on an input image and VGG16 for final classification based on the wrinkle information. Experiments of the proposed model are made with a data set that consists of 433 images rated by experts, showing the promising performance.