Recent advances in computer vision technologies have made possible the development of
intelligent monitoring systems for video surveillance and ambient-assisted living. By using …

We propose a novel architecture which is able to automatically anonymize faces in images
while retaining the original data distribution. We ensure total anonymization of all faces in an …

This paper presents critical surveillance system functions and considers advances and
challenges for privacy and ethical implications. We examine privacy-protection strategies …

In this paper, we propose a new face de-identification method based on generative
adversarial network (GAN) to protect visual facial privacy, which is an end-to-end method …

The increased use of sophisticated mobile devices opens up new possibilities and
challenges for language teachers and learners, which has led to an increasing need to …

This work addresses the problem of anonymizing the identity of faces in a dataset of images,
such that the privacy of those depicted is not violated, while at the same time the dataset is …

Privacy is one of the most important social and political issues in our information society,
characterized by a growing range of enabling and supporting technologies and services …

We demonstrate that modern image recognition methods based on artificial neural networks
can recover hidden information from images protected by various forms of obfuscation. The …

With an increasing number of users sharing information online, privacy implications entailing
such actions are a major concern. For explicit content, such as user profile or GPS data …

Privacy protection is a growing concern in the digital era, with machine vision techniques
widely used throughout public and private settings. Existing methods address this growing …