The performance of face analysis and recognition systems depends on the quality of the
acquired face data, which is influenced by numerous factors. Automatically assessing the …

Biometrics, an integral component of Identity Science, is widely used in several large-scale-
county-wide projects to provide a meaningful way of recognizing individuals. Among existing …

While COVID-19 has devastating effects on aviation, several recent studies have highlighted
the potential of the pandemic-induced break for rethinking air transportation, hopefully …

Noncontact biometrics such as face and iris have additional benefits over contact-based
biometrics such as fingerprint and hand geometry. However, three important challenges …

Something fundamental to computation-based research has really changed in the last ten
years. In certain fields, progress is simply dramatically more rapid than previously …

We propose a novel coupled mappings method for low resolution face recognition using
deep convolutional neural networks (DCNNs). The proposed architecture consists of two …

Deep neural network (DNN) architecture based models have high expressive power and
learning capacity. However, they are essentially a black box method since it is not easy to …

Biometric identity verification refers to technologies used to measure human physical or
behavioral characteristics, which offer a radical alternative to passports, ID cards, driving …

We propose a completely automatic approach for recognizing low resolution face images
captured in uncontrolled environment. The approach uses multidimensional scaling to learn …

We explore varying face recognition accuracy across demographic groups as a
phenomenon partly caused by differences in face illumination. We observe that for a …