Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

To understand the real world using various types of data, Artificial Intelligence (AI) is the
most used technique nowadays. While finding the pattern within the analyzed data …

One of the main challenges in feature learning using Deep Convolutional Neural Networks
(DCNNs) for large-scale face recognition is the design of appropriate loss functions that can …

The performance of face recognition system degrades when the variability of the acquired
faces increases. Prior work alleviates this issue by either monitoring the face quality in pre …

During COVID-19 coronavirus epidemic, almost everyone wears a mask to prevent the
spread of virus. It raises a problem that the traditional face recognition model basically fails …

With the recent world-wide COVID-19 pandemic, using face masks have become an
important part of our lives. People are encouraged to cover their faces when in public area to …

Racial equality is an important theme of international human rights law, but it has been
largely obscured when the overall face recognition accuracy is pursued blindly. More facts …

In recent years, visual recognition on challenging long-tailed distributions, where classes
often exhibit extremely imbalanced frequencies, has made great progress mostly based on …

Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …

A large number of intelligent models for masked face recognition (MFR) has been recently
presented and applied in various fields, such as masked face tracking for people safety or …