The rapid development of Artificial Intelligence (AI) technology has enabled the deployment
of various systems based on it. However, many current AI systems are found vulnerable to …

Given a facial matcher, in explainable face verification, the task is to answer: how relevant
are the parts of a probe image to establish the matching with an enrolled image. In many …

Abstract Several Remote Sensing applications in Hyperspectral Imaging rely on Artificial
Intelligence techniques, particularly Deep Neural Networks, which often outperform other …

Recently, face recognition systems have demonstrated remarkable performances and thus
gained a vital role in our daily life. They already surpass human face verification …

When explaining a recognition approach that can be used in facial analysis, eg, face
verification, face detection, attribute recognition, etc., the task is to answer: how relevant are …

Abstract Explainable Face Recognition is gaining growing attention as the use of the
technology is gaining ground in security-critical applications. Understanding why two face …

This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …

Recently, we have witnessed substantial success using the deep neural network in many
tasks. Although there still exist concerns about the explainability of decision making, it is …

During the COVID-19 coronavirus epidemic, wearing masks has become increasingly
popular. Traditional occlusion face recognition algorithms are almost ineffective for such …

In the past years, deep convolutional neural networks have been pushing the frontier of face
recognition (FR) techniques in both verification and identification scenarios. Despite the high …