Home| Journals | Statistics Online Expert | About Us | Contact Us
    About this Journal  | Table of Contents
Untitled Document

[Abstract] [PDF] [HTML] [Linked References]

International Journal of Statistika and Mathematika, ISSN: 2277- 2790 E-ISSN: 2249-8605

Volume 10, Issue 1, May 2014 pp 08-11

Research Article

Performance Evaluation of Statistical Approaches of Face Recognition Techniques

 

Ruzal N. Surti, Anjana Rodrigues

Electronics Department, MPSTME, Mumbai, Maharashtra, INDIA.


Academic Editor: Dr. Dase R.K.

 

Linked References

            1. N. Ahmed, T. Natarajan, and K. R. Rao. Discrete cosine transforms. IEEE Transactions on Computers, 23:90–93, 1974.
            2. D. Bhattacharjee, D. K. Basu, M. Nasipuri, and M. Kundu. Human face recognition using fuzzy multilayer perceptron. Soft Computing – A Fusion of Foundations, Methodologies and Applications, 14(6):559–570, April 2009.
            3. D. Cai, X.He, and J. Han. Semi-supervised discriminant analysis.Computer Vision. IEEE 11th International Conference on Computer Vision, 14:1–7, 2007.K. Elissa, “Title of paper if known,” unpublished.
            4. P. Comon. Independent component analysis, a new concept? Signal Processing, 36:287–314, 1994.
            5. J. G. Daugman. Two-dimensional spectral analysis of cortical receptive field profiles. Vision Research, 20(10):847 – 856, 1980.
            6. S. Kare, A. Samal, and D. Marx. Using bidimensional regression to assess face similarity. Machine Vision and Applications, 21(3):261–274, 2008.
            7. B. Kepenekci. Face recognition using Gabor Wavelet Transformation. PhD thesis, Te Middle East Technical University, September 2001.
            8. M. Kirby and L. Sirovich. Application of the karhunen-loeve procedure for the characterization of human faces. IEEE Transactions on Pattern Analysis and Machine Intelligence, 12(1):103–108, 1990.

 
 
 
 
 
  Copyrights statperson consultancy www

Copyrights statperson consultancy www.statperson.com  2013. All Rights Reserved.

Developer Details