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 …

Ever since man began domesticating animals several thousand years ago, we have always
relied on our intuition, collective knowledge, and sensory signals to make effective animal …

摘要近年来, 卷积神经网络(Convolutional neural networks, CNN) 已在图像理解领域得到了
广泛的应用, 引起了研究者的关注. 特别是随着大规模图像数据的产生以及计算机硬件(特别是 …

Unsupervised feature selection attempts to select a small number of discriminative features
from original high-dimensional data and preserve the intrinsic data structure without using …

Abstract Linear Discriminant Analysis (LDA) assumes that all samples from the same class
are independently and identically distributed (iid). LDA may fail in the cases where the …

Face recognition constitutes a relatively a popular area which has emerged from the rulers
of the social media to top universities in the world. Those frontiers and rule makers recently …

Exploration of optoelectronic memristors with the capability to combine sensing and
processing functions is required to promote development of efficient neuromorphic vision. In …

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

The recent developments in the modern data collection tools, techniques, and storage
capabilities are leading towards huge volume of data. The dimensions of data indicate the …

Face recognition technology is a biometric technology, which is based on the identification
of facial features of a person. People collect the face images, and the recognition equipment …