Anonymization methods have gained widespread use in safeguarding privacy. However,
conventional anonymization solutions inevitably lead to the loss of semantic information …

The success of deep learning based face recognition systems has given rise to serious
privacy concerns due to their ability to enable unauthorized tracking of users in the digital …

A number of applications (eg, video surveillance and authentication) rely on automated face
recognition to guarantee functioning of secure services, and meanwhile, have to take into …

The advancement of face recognition technology has delivered substantial societal
advantages. However, it has also raised global privacy concerns due to the ubiquitous …

Nowadays, privacy issue has become a top priority when training AI algorithms. Machine
learning algorithms are expected to benefit our daily life, while personal information must …

Although the current generative adversarial networks (GAN)-generated face forensic
detectors based on deep neural networks (DNNs) have achieved considerable …

Face privacy Preservation is research subject has attracted significant interest. Existing face
privacy-preserving methods aim at erasing the semantic information of faces; however, they …

The unprecedented capture and application of face images raise increasing concerns on
anonymization to fight against privacy disclosure. Most existing methods may suffer from the …

Falls are a major concern for people with Parkinson's disease (PwPD), but accurately
assessing real-world fall risk beyond the clinic is challenging. Contemporary technologies …

In recent years, the increasing availability of personal data has raised concerns regarding
privacy and security. One of the critical processes to address these concerns is data …