DocumentCode
3158295
Title
Face recognition using a hybrid supervised/unsupervised neural network
Author
Intrator, Nathan ; Reisfeld, Daniel ; Yeshurun, Yehezkel
Author_Institution
Dept. of Comput. Sci., Tel Aviv Univ., Israel
Volume
2
fYear
1994
fDate
9-13 Oct 1994
Firstpage
50
Abstract
Face recognition schemes that are applied directly to gray level pixel images are presented. Two methods for reducing the overfitting-a common problem in high dimensional classification schemes-are presented and the superiority of their combination is demonstrated. The classification scheme is preceded by preprocessing devoted to reducing the viewpoint and scale variability in the data
Keywords
face recognition; face recognition; facial normalisation; feature extraction; gray level pixel images; high dimensional classification; hybrid supervised/unsupervised neural network; scale variability; Artificial neural networks; Computer science; Degradation; Face recognition; Image recognition; Neural networks; Pixel; Plastics; Robustness; Unsupervised learning;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 1994. Vol. 2 - Conference B: Computer Vision & Image Processing., Proceedings of the 12th IAPR International. Conference on
Conference_Location
Jerusalem
Print_ISBN
0-8186-6270-0
Type
conf
DOI
10.1109/ICPR.1994.576874
Filename
576874
Link To Document