Deep Convolutional Neural Network Used in Single Sample per Person Face Recognition
نویسندگان
چکیده
منابع مشابه
Low-resolution face recognition with single sample per person
As a growing number of low-resolution (LR) face images are captured by surveillance cameras, LR face recognition has been a hot issue for recent years. Previous efforts on LR face recognition typically assume each subject has multiple high-resolution (HR) training samples. However, this assumption may not hold in some special cases such as law-enforcement where only a single HR sample per perso...
متن کاملFace Recognition from One Sample per Person
As one of the most visible applications in computer vision communication, face recognition (FR) has become significant role in the community. In the past decade, researchers have been devoting themselves to addressing the various problems emerging in practical FR applications in uncontrolled or less controlled environment. In many practical applications of FR (e.g., law enforcement, e-passport,...
متن کاملDomain-Specific Face Synthesis for Video Face Recognition from a Single Sample Per Person
In video surveillance, face recognition (FR) systems are employed to detect individuals of interest appearing over a distributed network of cameras. The performance of still-tovideo FR systems can decline significantly because faces captured in the unconstrained operational domain (OD) over multiple video cameras have a different underlying data distribution compared to faces captured under con...
متن کاملEfficiency of Recognition Methods for Single Sample per Person Based Face Recognition
Even for the present-day computer technology, the biometric recognition of human face is a difficult task and continually evolving concept in the area of biometric recognition. The area of face recognition is well-described today in many papers and books, e.g. (Delac et al., 2008), (Li & Jain, 2005), (Oravec et al., 2010). The idea that two-dimensional still-image face recognition in controlled...
متن کاملFace recognition: a convolutional neural-network approach
We present a hybrid neural-network for human face recognition which compares favourably with other methods. The system combines local image sampling, a self-organizing map (SOM) neural network, and a convolutional neural network. The SOM provides a quantization of the image samples into a topological space where inputs that are nearby in the original space are also nearby in the output space, t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Intelligence and Neuroscience
سال: 2018
ISSN: 1687-5265,1687-5273
DOI: 10.1155/2018/3803627