Synthetic data is emerging as a substitute for authentic data to solve ethical and legal
challenges in handling authentic face data. The current models can create real-looking face …

Facial recognition is one of the most academically studied and industrially developed areas
within computer vision where we readily find associated applications deployed globally. This …

The development of deep learning algorithms has extensively empowered humanity's task
automatization capacity. However, the huge improvement in the performance of these …

Face recognition systems are susceptible to differences in performance across demographic
or non-demographic groups. However, the understanding of the behavior of face recognition …

Today, the significance of biometrics is more pronounced than ever in accurately allowing
access to valuable resources, from personal devices to highly sensitive buildings, as well as …

In response to the breakout of the CoViD-19 pandemic and the resulting face mask
mandates, interest has surged in the development of face mask detection algorithms for …

The wide focus on deep learning in the last decade led to the development of models with a
great capacity to perform complex tasks. While allowing for efficient task automatization …

How do human sources of social bias introduce and exacerbate inequalities in automated
face classification? In this dissertation, I discuss existing work on demographic bias in …