Models and Methods for Solving Face Recognition Problem by Photos

Proceedings of the 21st International Workshop on Computer Science and Information Technologies (CSIT 2019) ◽

10.2991/csit-19.2019.41 ◽

2019 ◽

Author(s):

Farit Gabdiev ◽

Nafisa Yusupova ◽

Olga Smetanina ◽

Ekaterina Sazonova

Keyword(s):

Face Recognition ◽

Recognition Problem

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On a development of sparse PCA method for face recognition problem

10.1109/atc52653.2021.9598326 ◽

2021 ◽

Author(s):

Loc Tran ◽

Bich Ngo ◽

Tuan Tran ◽

Lam Pham ◽

An Mai

Keyword(s):

Face Recognition ◽

Recognition Problem ◽

Sparse Pca ◽

Pca Method

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A Comparison of Features Spaces for Face Recognition Problem

2006 IEEE 14th Signal Processing and Communications Applications ◽

10.1109/siu.2006.1659818 ◽

2006 ◽

Author(s):

G.T. Ozyer ◽

E. Akbas ◽

F.Y. Vural

Keyword(s):

Face Recognition ◽

Recognition Problem

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A study of fuzzy logic ensemble system performance on face recognition problem

IOP Conference Series Materials Science and Engineering ◽

10.1088/1757-899x/173/1/012013 ◽

2017 ◽

Vol 173 ◽

pp. 012013 ◽

Cited By ~ 6

Author(s):

A Polyakova ◽

L Lipinskiy

Keyword(s):

Fuzzy Logic ◽

Face Recognition ◽

System Performance ◽

Recognition Problem

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Very low resolution face recognition problem

2010 Fourth IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS) ◽

10.1109/btas.2010.5634490 ◽

2010 ◽

Cited By ~ 101

Author(s):

W. W. Zou Wilman ◽

Pong C. Yuen

Keyword(s):

Face Recognition ◽

Recognition Problem ◽

Low Resolution

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Nonrigid Registration Algorithm in the Face Recognition Problem

Journal of Communications Technology and Electronics ◽

10.1134/s1064226921120160 ◽

2021 ◽

Vol 66 (12) ◽

pp. 1452-1459

Author(s):

A. Yu. Makovetskii ◽

V. I. Kober ◽

S. M. Voronin ◽

A. V. Voronin ◽

V. N. Karnaukhov ◽

...

Keyword(s):

Face Recognition ◽

Recognition Problem ◽

Nonrigid Registration ◽

Registration Algorithm ◽

The Face

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Using Rough Set in Feature Selection and Reduction in Face Recognition Problem

Advances in Knowledge Discovery and Data Mining - Lecture Notes in Computer Science ◽

10.1007/11430919_28 ◽

2005 ◽

pp. 226-233 ◽

Cited By ~ 6

Author(s):

Le Hoai Bac ◽

Nguyen Anh Tuan

Keyword(s):

Feature Selection ◽

Face Recognition ◽

Rough Set ◽

Recognition Problem

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A comparative study of feature extraction methods and their application to P-RBF NNs in face recognition problem

Fuzzy Sets and Systems ◽

10.1016/j.fss.2015.11.018 ◽

2016 ◽

Vol 305 ◽

pp. 131-148 ◽

Cited By ~ 3

Author(s):

Sung-Kwun Oh ◽

Sung-Hoon Yoo ◽

Witold Pedrycz

Keyword(s):

Feature Extraction ◽

Face Recognition ◽

Comparative Study ◽

Extraction Methods ◽

Recognition Problem

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On solving the face recognition problem with one training sample per subject

Pattern Recognition ◽

10.1016/j.patcog.2006.03.010 ◽

2006 ◽

Vol 39 (9) ◽

pp. 1746-1762 ◽

Cited By ~ 69

Author(s):

Jie Wang ◽

K.N. Plataniotis ◽

Juwei Lu ◽

A.N. Venetsanopoulos

Keyword(s):

Face Recognition ◽

Training Sample ◽

Recognition Problem ◽

The Face

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An Exploratory Model for Face Recognition Problem in Autism: An Artificial Neural Network Approach

Journal of Neurodevelopmental Cognition ◽

10.29252/jncog.1.2.42 ◽

2019 ◽

Vol 2 (1) ◽

pp. 42-56

Author(s):

Shima Nofallah ◽

Fatemeh Bakouie ◽

Amirhossein Memari ◽

Shahriar Gharibzadeh

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Face Recognition ◽

Recognition Problem ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Artificial Neural Network Approach ◽

Exploratory Model

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Customized orthogonalization via deflation algorithm with applications in face recognition

Carpathian Journal of Mathematics ◽

10.37193/cjm.2014.02.05 ◽

2014 ◽

Vol 30 (2) ◽

pp. 231-238

Author(s):

LACRAMIOARA (LITA) GRECU ◽

◽

ELENA PELICAN ◽

Keyword(s):

Computer Vision ◽

Face Recognition ◽

Dimension Reduction ◽

Linear Algebra ◽

Numerical Linear Algebra ◽

Recognition Problem ◽

Topical Issue ◽

Standard Algorithm ◽

The Face ◽

Reduction Methods

The face recognition problem is a topical issue in computer vision. In this paper we propose a customized version of the orthogonalization via deflation algorithm to tackle this problem. We test the new proposed algorithm on two datasets: the well-known ORL dataset and an own face dataset, CTOVF; also, we compare our results (in terms of rate recognition and average quiery time) with the outcome of a standard algorithm in this class (dimension reduction methods using numerical linear algebra tools).

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