Affiliation:
1. FIRAT ÜNİVERSİTESİ, FEN BİLİMLERİ ENSTİTÜSÜ
2. FIRAT ÜNİVERSİTESİ, MÜHENDİSLİK FAKÜLTESİ
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.
Reference15 articles.
1. Bahar MS, Buluş E. Derin Öğrenme Teknikleri Kullanılarak Sahte Yüz Fotoğrafı ve Videosu Sentezi. Düzce Üniversitesi Bilim ve Teknoloji Dergisi 2021; 9(6): 354-369. DOI: 10.29130/dubited.1017584.
2. Sabour S, Frosst N, Hinton GE. Dynamic Routing Between Capsules. arXiv preprint 2017; arXiv:1710.09829.
3. Kizrak MA, Beser F, Bolat B, Yildirim T. Kapsül Ağları ile İşaret Dili Tanıma Recognition of Sign Language using Capsule Networks. 26th Signal Processing and Communications Applications Conference (SIU) 2018; 1-4. doi:10.1109/SIU.2018.8404385.
4. Osman AA, Face Identification Using Capsule Network with Small Data Set. Master Thesis, Tallin University of Technology, 2020.
5. Salman, FM, Abu-Naser, SS. Classification of Real and Fake Human Faces Using Deep Learning. International Journal of Academic Engineering Research (IJAER) (2022); 6 (3):1-14.