Classification of Real and Fake Face Data Using Capsule Networks

Abstract

Recently, with the advancement of technology, artificial intelligence has begun to be used in many areas. It is used in many fields such as artificial intelligence, image processing, natural language processing, suggestion systems. The increase in the use of artificial intelligence has revealed the need for data. This situation has led to the production of new data from existing data. Today, generative adversarial networks (GAN) synthesize a wide variety of data inspired by existing data. These fake data produced from real image data can sometimes cause undesirable situations. It is an important issue to know whether the images, which are especially important for security, are fake or not. In this study, the classification of real human face data and fake face data generate from these data has been made. Fake face data were generated with the help of StyleGAN2-ADA from a small-sized dataset created by collecting facial data of a famous person. It is aimed to classify the generated fake face data and real face data with the capsule network model.