Recent advancements in deep learning generative models have raised concerns as they
can create highly convincing counterfeit images and videos. This poses a threat to people's …

Deep learning has become a predominant method for solving data analysis problems in
virtually all fields of science and engineering. The increasing complexity and the large …

The emerging field of privacy-preserving biometrics is attracting significant attention, as a
paradigm that can address several of the key concerns in cryptographic authentication …

In recent years, the exponential growth of internet technologies has made personal
authentication an integral part of security applications. The fingerprint-based biometric …

Deep Learning algorithms (DL) have been applied in different domains such as computer
vision, image detection, robotics and speech processing, in most cases, DL demonstrated …

Fingerprint-based biometric systems have elevated industrial standards worldwide through
rapid personal verification. The array of identity frauds and cyber-attacks have also …

Touchless biometrics, particularly touchless fingerprint recognition, have gained significant
attention in recent years, with the COVID-19 pandemic accelerating the need for clean and …

Biometrics is a technique used to define, assess, and quantify a person's physical and
behavioral property. In recent history, deep learning has shown impressive progress in …

Performance of the state-of-the-art fingerprint denoising model on poor-quality fingerprints
degrades due to cross-domain shift observed between training and testing domains. To …

Double-identity biometrics, that is the combination of two subjects' features into a single
template, was demonstrated to be a serious threat against existing biometric systems. In fact …