The accuracies for many pattern recognition tasks have increased rapidly year by year,
achieving or even outperforming human performance. From the perspective of accuracy …

Abstract Deep Convolutional Neural Networks (CNNs) have been pushing the frontier of
face recognition over past years. However, existing CNN models are far less accurate when …

With the recent advancement of deep convolutional neural networks, significant progress
has been made in general face recognition. However, the state-of-the-art general face …

Recently, regression analysis has become a popular tool for face recognition. Most existing
regression methods use the one-dimensional, pixel-based error model, which characterizes …

Robust sparse representation has shown significant potential in solving challenging
problems in computer vision such as biometrics and visual surveillance. Although several …

Recently the sparse representation based classification (SRC) has been proposed for robust
face recognition (FR). In SRC, the testing image is coded as a sparse linear combination of …

Deployment of PV generation has been recognized as one of the promising measures taken
for mitigating the environmental issues worldwide. To seamlessly integrate PV and other …

In this paper, we study the problem of robust feature extraction based on l 2, 1 regularized
correntropy in both theoretical and algorithmic manner. In theoretical part, we point out that …

In graph embedding based methods, we usually need to manually choose the nearest
neighbors and then compute the edge weights using the nearest neighbors via L2 norm (eg …

A sparse representation-based classifier (SRC) is developed and shows great potential for
real-world face recognition. This paper presents a dimensionality reduction method that fits …