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 performance of a biometric system that relies on a single biometric modality (eg,
fingerprints only) is often stymied by various factors such as poor data quality or limited …

In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …

Systems incorporating biometric technologies have become ubiquitous in personal,
commercial, and governmental identity management applications. Both cooperative (eg …

Iris recognition refers to the automated process of recognizing individuals based on their iris
patterns. The seemingly stochastic nature of the iris stroma makes it a distinctive cue for …

Biometric authentication technology has become increasingly common in our daily lives as
information protection and control regulation requirements have grown worldwide. A …

Over the past two decades, biometric recognition has exploded into a plethora of different
applications around the globe. This proliferation can be attributed to the high levels of …

With the rapid development of the Mobile Internet and the Industrial Internet of Things, a
variety of applications put forward an urgent demand for user and device identity …

Iris segmentation is a critical step for improving the accuracy of iris recognition, as well as for
medical concerns. Existing methods generally use whole eye images as input for network …

This paper proposes an accurate and generalizable deep learning framework for iris
recognition. The proposed framework is based on a fully convolutional network (FCN), which …