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To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of “closed set” recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is “open set” recognition, where incomplete knowledge of the(More)
Face recognition in unconstrained environments is one of the most challenging problems in biometrics. One vexing problem in unconstrained environments is that of scale; a face captured at large distances is considerably harder to recognize than the same face at small distances. Several methods have been proposed to tackle unconstrained face recognition in a(More)
This paper addresses large scale, unconstrained, open set face recognition, which exhibits the properties of operational face recognition scenarios. Most of the existing face recognition databases have been designed under controlled conditions or have been constructed from the images collected from the web. Face images collected from the web are less(More)
Scale is one of the major challenges in recognition problems. For example, a face captured across large distances is considerably harder to recognize than the same face at small distances. Local binary pattern (LBP) and its variants have been successfully used in face detection, recognition, and many other computer vision applications. While LBP features(More)
While modern research in face recognition has focused on new feature representations, alternate learning methods for fusion of features, most have ignored the issue of unmodeled correlations in face data when combining diverse features such as similar visual regions, attributes, appearance frequency, etc. Conventional wisdom is that by using sufficient data(More)
Inelastic neutron scattering measurements of paramagnetic SrCo2As2 at T=5 K reveal antiferromagnetic (AFM) spin fluctuations that are peaked at a wave vector of Q(AFM)=(1/2,1/2,1) and possess a large energy scale. These stripe spin fluctuations are similar to those found in AFe2As2 compounds, where spin-density wave AFM is driven by Fermi surface nesting(More)
We use nuclear magnetic resonance (NMR), high-resolution x-ray, and neutron scattering studies to study structural and magnetic phase transitions in phosphorus-doped BaFe2(As(1-x)P(x)2. Previous transport, NMR, specific heat, and magnetic penetration depth measurements have provided compelling evidence for the presence of a quantum critical point (QCP) near(More)
A hallmark of the iron-based superconductors is the strong coupling between magnetic, structural and electronic degrees of freedom. However, a universal picture of the normal state properties of these compounds has been confounded by recent investigations of FeSe where the nematic (structural) and magnetic transitions appear to be decoupled. Here, using(More)
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