Forensic Application

Forensic applications of image and audio analysis are rapidly evolving to address the challenges posed by increasingly sophisticated methods of media manipulation and forgery. Current research focuses on developing robust detection methods, often employing deep learning architectures like convolutional neural networks and transformers, to identify AI-generated content, localized manipulations, and inconsistencies in metadata. These advancements are crucial for maintaining the integrity of digital evidence in legal and investigative contexts, as well as combating the spread of misinformation. The field also emphasizes the development of counter-forensic techniques to understand vulnerabilities and improve the resilience of detection methods.