Deep learning-based face recognition models are vulnerable to adversarial attacks. In
contrast to general noises, the presence of imperceptible adversarial noises can lead to …

Abstract The Broad Learning System (BLS) employs two successive random feature
mappings and incorporates ridge regression to construct an efficient classifier. This system …

In this paper we address the vulnerabilities of iris recognition systems to both image-based
impersonation attacks and Presentation Attacks (PAs) in physical environments. While …

To harness the power of pre-trained image classification models on the extensive ImageNet
dataset, early layers of pre-trained backbones have been used to capture relevant …

Deep neural networks have proven to be highly effective in the face recognition task, as they
can map raw samples into a discriminative high-dimensional representation space …

Deep learning-based single-image infrared (IR) destriping has made significant advances.
However, these methods are typically evaluated using “synthetic” images with specific stripe …

Iris recognition technology plays a critical role in biometric identification systems, but their
performance can be affected by variations in iris pigmentation. In this work, we investigate …

This study presents a human identity authentication framework that integrates facial
recognition and biometric scanning, enhancing security and speeding up individual …

Nowadays, advancements in facial recognition technology necessitate robust solutions to
address challenges in real-world scenarios, including lighting variations and facial position …