Biometric recognition refers to the automated recognition of individuals based on their
biological and behavioral characteristics such as fingerprint, face, iris, and voice. The first …

Today, digitalization decisively penetrates all the sides of the modern society. One of the key
enablers to maintain this process secure is authentication. It covers many different areas of a …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

Face recognition is a mainstream biometric authentication method. However, the
vulnerability to presentation attacks (aka spoofing) limits its usability in unsupervised …

The vulnerability of face recognition systems to presentation attacks (also known as direct
attacks or spoof attacks) has received a great deal of interest from the biometric community …

The revolution in computer hardware, especially in graphics processing units and tensor
processing units, has enabled significant advances in computer graphics and artificial …

The use of human finger-vein traits for the purpose of automatic user recognition has gained
a lot of attention in recent years. Current state-of-the-art techniques can provide relatively …

In recent decades, we have witnessed the evolution of biometric technology from the first
pioneering works in face and voice recognition to the current state of development wherein a …

Speech is a powerful medium of communication that always convey rich and useful
information, such as gender, accent, and other unique characteristics of a speaker. These …

Temporal features is important for face anti-spoofing. Unfortunately existing methods have
limitations to explore such temporal features. In this work, we propose a deep neural …