Face recognition is an efficient technique and one of the most preferred biometric modalities
for the identification and verification of individuals as compared to voice, fingerprint, iris …

Future wireless communications are becoming increasingly complex with different radio
access technologies, transmission backhauls, and network slices, and they play an …

In the field of image set classification, most existing works focus on exploiting effective latent
discriminative features. However, it remains a research gap to efficiently handle this …

Deep neural network approaches have made remarkable progress in many machine
learning tasks. However, the latest research indicates that they are vulnerable to adversarial …

Facing the challenge of distributed computing on processing large-scale data, this paper
proposes a consensus-based decentralized training method with communication …

Large-scale face identification or 1-to-N matching where N is huge, plays a vital role in
biometrics and surveillance. The system demands accurate and speedy matching where …

Face recognition is an important task in both academia and industry. With the development
of deep convolutional neural networks, many deep face recognition methods have been …

Technology is getting smarter day by day and facilitating every part of human life from
automatic alarming, automatic temperature, and personalised choice prediction and …

Face recognition in general scenarios has been saturated in recent years, but there is still
room to enhance model performance in extreme scenarios and fairness situations. Inspired …

Increasing inter-class variance and shrinking intra-class distance are two main concerns
and efforts in face recognition. In this paper, we propose a new loss function termed inter …