In the context of 2D face biometrics, pose represents one challenging intra-class variation
that, over the years, has been approached in a number of different ways, such as through …

A face recognition system that uses 3-D lighting estimation and optimal lighting
compensation for dark-field application is proposed. To develop the proposed system, which …

Face recognition is a thriving topic in biometrics literature. In most cases, it is performed on
RGB images using deep learning approaches. However, due to the wider scenarios in …

Face recognition has been deeply studied and widely used in recent years. A novel method,
called local gradient number pattern (LGNP), is firstly presented in the paper for face …

In near decades machine learning approaches have received overwhelming attention from
many researchers for solving problems that cannot be ironed out by traditional approaches …

In recent times, most of the Facial Recognition framework has shown better outcomes in a
constrained environment. Due to its high usage, the FR has gained increased attention in …

Extreme learning machine (ELM) is a powerful classification method and is very competitive
among existing classification methods. It is speedy at training. Nevertheless, it cannot …

This paper presents a lightweight Convolutional Neural Network (CNN) model for face
recognition. The network structure has three convolutional layers, three pooling layers, one …

This work proposes a novel generative model, FF-GAN (Frontal Face Generative Adversarial
Network), for generating high-quality and diverse frontal faces. FF-GAN utilizes contrastive …

The Generalized Adaptive Resonance Theory (GART) model is a supervised online learning
neural network based on an integration of Adaptive Resonance Theory (ART) and the …