Results 171 to 180 of about 3,640,145 (204)

Fast Non-Negative Matrix Factorizations for Face Recognition

International Journal of Pattern Recognition and Artificial Intelligence, 2017
Non-negative Matrix Factorization (NMF), as a promising image-data representation approach, encounters the problems of slow convergence and weak classification ability. To overcome these limitations, this paper, based on different error measurements, proposes two kinds of NMF algorithms with fast gradient descent and high discriminant performance.
Wen-Sheng Chen, Yugao Li, Binbin Pan, Chen Xu   +3 more
openaire   +2 more sources

Topology Preserving Non-negative Matrix Factorization for Face Recognition

IEEE Transactions on Image Processing, 2008
In this paper, a novel topology preserving non-negative matrix factorization (TPNMF) method is proposed for face recognition. We derive the TPNMF model from original NMF algorithm by preserving local topology structure. The TPNMF is based on minimizing the constraint gradient distance in the high-dimensional space.
T, Zhang, B, Fang, Y Y, Tang, G, He, J, Wen   +4 more
openaire   +2 more sources

Face recognition via weighted non-negative sparse representation

2021
Face recognition is one of the most important tools of identification in biometrics. Face recognition has attracted great attention in the last decades and numerous algorithms have been proposed. Different researches have shown that face recognition with Sparse Representation based Classification (SRC) has great classification performance.
Khosravi, Hoda, Ghaffari, Aboozar, Vahidi, Javad   +2 more
openaire   +1 more source

Chemical Firms Face Negative Debt Ratings

Chemical & Engineering News Archive, 2003
T he deterioration of credit quality among North American chemical companies continued throughout the second quarter, according to a new report by Standard & Poor's Rating Services. Year-to-date, downgrades have outpaced upgrades 20 to 1, continuing a multiyear slide in credit quality.
openaire   +1 more source

Non-negative Matrix Factorization for Face Recognition

2002
The computer vision problem of face classification under several ambient and unfavorable conditions is considered in this study. Changes in expression, different lighting conditions and occlusions are the relevant factors that are studied in this present contribution.
David Guillamet, Jordi Vitrià
openaire   +1 more source

Discriminant non-negative graph embedding for face recognition

Neurocomputing, 2015
Abstract Non-negative Matrix Factorization (NMF) is an unsupervised algorithm for low-rank approximation of non-negative data and has been widely used in many fields, but its performance in feature extraction is not satisfactory. The main reason is that the model of NMF and its variants did not take into account the label information of the samples ...
Jinrong Cui, Jiajun Wen, Zhengming Li, Li Bin   +3 more
openaire   +1 more source

Brain and behavioral inhibitory control of kindergartners facing negative emotions

Developmental Science, 2015
AbstractInhibitory control (IC) – one of the most critical functions underlying a child's ability to self‐regulate – develops significantly throughout the kindergarten years. Experiencing negative emotions imposes challenges on executive functioning and may specifically affect IC.
Tali, Farbiash, Andrea, Berger
openaire   +2 more sources

Non-negative Compatible Kernel Construction for Face Recognition

2015
The existing Kernel Nonnegative Matrix Factorization (KNMF) cannot ensure the non-negativity of the mapped data in the kernel feature space. This is called the nonnegative in-compatible problem of KNMF. To tackle this problem, this paper presents a new methodology to construct Nonnegative Compatible Kernel (NC-Kernel) for face recognition.
Yang Zhao, Wensheng Chen, Binbin Pan, Bo Chen   +3 more
openaire   +1 more source

Face Recognition with Multi-Tone and Two-Tone Photographic Negatives

Perception, 1997
The effects of photographic negatives on face recognition are often studied in two different ways—faces are learned and tested in photographic negatives (NN) or the contrast is reversed between learning and testing, ie they are learned in positives and tested in negatives (PN) or vice versa (NP).
C H, Liu, A, Chaudhuri
openaire   +2 more sources

Second‐in‐command faces negative reviews after complaining

Campus Legal Advisor, 2017
Case name: Torregiano v. Monroe Community College, No. 11‐CV‐6300 (W.D. N.Y. 10/26/15).
openaire   +1 more source