Successful integration of deep neural networks (DNNs) or deep learning (DL) has resulted
in breakthroughs in many areas. However, deploying these highly accurate models for data …

Lightweight deep convolutional neural networks (LDCNNs) are vital components of mobile
intelligence, particularly in mobile vision. Although various heavy networks with increasingly …

In this paper, we contribute a new million-scale face benchmark containing noisy 4M
identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) …

Edge intelligence refers to a set of connected systems and devices for data collection,
caching, processing, and analysis proximity to where data are captured based on artificial …

As an emerging topic in face recognition, designing margin-based loss functions can
increase the feature margin between different classes for enhanced discriminability. More …

Face recognition is a prevailing authentication solution in numerous biometric applications.
Physical adversarial attacks, as an important surrogate, can identify the weaknesses of face …

Background and objective Facial expression recognition technology will play an
increasingly important role in our daily life. Autonomous driving, virtual reality and all kinds …

The development of deep learning-based biometric models that can be deployed on devices
with constrained memory and computational resources has proven to be a significant …

Using the face as a biometric identity trait is motivated by the contactless nature of the
capture process and the high accuracy of the recognition algorithms. After the current COVID …

Mechanical fault diagnosis is one of the important technologies in the fourth industrial
revolution. In recent years, mechanical fault diagnosis based on audio signal analysis …