Sketch to Face Generation Using GAN for Suspect Identification

At a time when privacy concerns and civil liberties are paramount, this study explores the motivations and implications of using face recognition in criminal investigations, specifically through the application of Generative Adversarial Networks (GANs) to crime in the study of the. This project is based on the automatic facial recognition of criminals or specific targets using machine learning. Given a set of features to the Generative Adversarial Network (GAN), the algorithm generates an image of the target with the specified feature set. The paper analyzes and compares the work done so far on crime analysis and how to use GANs. This paper also highlights how the model resolves issues with the potential advantages and challenges of the technology emphasized. It emphasizes the need to balance security and privacy rights when using facial recognition in criminal cases. Finally, this research paper provides valuable insights into the developments and potential opportunities associated with the use of facial generation through sketch technology in criminal justice in the coming years.