This article presents FRCSyn-onGoing, an ongoing challenge for face recognition where
researchers can easily benchmark their systems against the state of the art in an open …

Large-scale face recognition datasets are collected by crawling the Internet and without
individuals' consent, raising legal, ethical, and privacy concerns. With the recent advances in …

Large Language Models (LLMs) such as GPT developed by OpenAI, have already shown
astonishing results, introducing quick changes in our society. This has been intensified by …

Recent advances in deep face recognition have spurred a growing demand for large,
diverse, and manually annotated face datasets. Acquiring authentic, high-quality data for …

Object detection is a basic vision task that accompanies people's daily lives all the time. The
development of object detection technology has experienced an evolution from traditional …

EXplainable Artificial Intelligence (XAI) approaches are widely applied for identifying
fairness issues in Artificial Intelligence (AI) systems. However, in the context of facial …

We present a novel metric designed, among other applications, to quantify biased behaviors
of machine learning models. As its core, the metric consists of a new similarity metric …

Over the recent years, the advancements in deep face recognition have fueled an increasing
demand for large and diverse datasets. Nevertheless, the authentic data acquired to create …

A robust face recognition model must be trained using datasets that include a large number
of subjects and numerous samples per subject under varying conditions (such as pose …

Monitoring and updating attendance records of students is an integral part of activities in
schools and colleges. To mitigate the laborious work of keeping attendance records, an …