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 …

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 …

We propose a two-stage deep residual attention generative adversarial network (TSDRA-
GAN) for inpainting iris textures obscured by eyelids. This two-stage generation approach …

Iris Recognition (IR) is one of the market's most reliable and accurate biometric systems.
Today, it is challenging to build NearInfraRed (NIR) capturing devices under the premise of …

Fitness for Duty (FFD) techniques detects whether a subject is Fit to perform their work
safely, which means no reduced alertness condition and security, or if they are Unfit, which …

Background Recruitment and retention of participants in research studies conducted in
fishing communities remain a challenge because of population mobility. Reliable and …

In biometric identification, iris recognition is a non-contact identification method with higher
significance. The images used for validation are attained from the visible light camera or …

The segmentation of reflections from the iris region is a relevant task for biometric systems,
human-machine inter-action technologies, and photo editing applications. This task is …

Iris recognition technology has attracted an increasing interest in the last decades in which
we have witnessed a migration from research laboratories to real-world applications. The …

Iris recognition is a prominent technique in biometric identification due to its robustness and
distinctive features. However, challenges in iris segmentation, including limitation of …