Principal component analysis is a versatile statistical method for reducing a cases-by-
variables data table to its essential features, called principal components. Principal …

Face recognition is one of the most active research fields of computer vision and pattern
recognition, with many practical and commercial applications including identification, access …

随着大数据时代的到来, 含更多隐含层的深度卷积神经网络(Convolutional neural networks,
CNNs) 具有更复杂的网络结构, 与传统机器学习方法相比具有更强大的特征学习和特征表达 …

GAN inversion aims to invert a given image back into the latent space of a pretrained GAN
model so that the image can be faithfully reconstructed from the inverted code by the …

Over the past few decades, interest in theories and algorithms for face recognition has been
growing rapidly. Video surveillance, criminal identification, building access control, and …

Multiview learning (MVL), which enhances the learners' performance by coordinating
complementarity and consistency among different views, has attracted much attention. The …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

A review of developments in the rapidly developing field of deep learning is presented.
Recommendations are made for original contributions to the literature, as opposed to …

Deep learning applies multiple processing layers to learn representations of data with
multiple levels of feature extraction. This emerging technique has reshaped the research …

These days, face recognition systems are widely being employed in various daily
applications such as smart phone unlocking, tracking school attendance, and secure online …