DeIdentification Tool

De-identification tools aim to remove personally identifiable information from data while preserving its utility for research and analysis. Current research focuses on improving the accuracy and reproducibility of these tools across diverse data types, including text, images (like driver's face videos), and audio, employing techniques such as generative adversarial networks (GANs) and various signal processing algorithms for voice modification. The development of robust and reliable de-identification methods is crucial for responsible data sharing, enabling collaborative research while protecting individual privacy and promoting ethical data practices across various scientific disciplines.