Jan. 27, 2022, 2:20 a.m. | Sachith Seneviratne, Nuran Kasthuriarachchi, Sanka Rasnayaka, Danula Hettiachchi, Ridwan Shariffdeen

cs.CR updates on arXiv.org arxiv.org

Contactless and efficient systems are implemented rapidly to advocate
preventive methods in the fight against the COVID-19 pandemic. Despite the
positive benefits of such systems, there is potential for exploitation by
invading user privacy. In this work, we analyse the privacy invasiveness of
face biometric systems by predicting privacy-sensitive soft-biometrics using
masked face images. We train and apply a CNN based on the ResNet-50
architecture with 20,003 synthetic masked images and measure the privacy
invasiveness. Despite the popular belief of …

deep learning images privacy protect

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