Detection and Attribution of Synthetically Generated Deepfake Imagery

This thesis examines the automated recognition of AI-generated photographs of non-existent people. It prioritises the development of attribution methods to identify the creators behind these potentially hazardous images, using subtle imperfections within them as fingerprint patterns. It also proposes and evaluates a concise, modular solution using transfer learning, enabling increased efficiency, expandability, and external validity.