Computer Vision has come a long way after the introduction of Convolutional Neural
Networks, that simulated the first perception layers in the human vision, specially in …

Although CNNs are widely used in vision tasks and achieve high accuracies, they can still
fail on unseen data as they handle images quite differently than the brain. CNNs do not …

This article first briefly introduces the face recognition system. By improving the traditional
model of the SSD network, the lightweight MobileNet network model replaces the original …

In order to avoid overfitting of face recognition results in complex Convolutional Neural
Network (CNN) on small and medium face situation, this paper provides a face recognition …

This study introduces a technique for facial recognition according to capsule networks. The
system utilizes the advantages of capsule networks to model the face features in the image …

Face recognition (FR) is a technique for recognizing individuals through the use of face
photographs. The FR technology is widely applicable in a variety of fields, including security …

Currently, many famous convolutional neural networks depend on massive training samples
and high-performance computers. To solve this problem, this paper improves the deep …

This paper reviews the latest state of face recognition technology and applications. Provides
a brief background of face recognition and specific algorithms, including Region-CNN (R …

In epidemic situations such as the novel coronavirus disease (COVID-19) pandemic that
spreads through physical contact, security and presence systems that previously used …

Technology of face recognition has developed rapidly in the past three decades. Various
face recognition methods have been proposed by a lot of research. The primary objective of …