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PR
2008
87views more  PR 2008»
8 years 9 months ago
Two-dimensional Laplacianfaces method for face recognition
In this paper we propose a two-dimensional (2D) Laplacianfaces method for face recognition. The new algorithm is developed based on two techniques, i.e., locality preserved embedd...
Ben Niu, Qiang Yang, Simon Chi-Keung Shiu, Sankar ...
PCM
2007
Springer
169views Multimedia» more  PCM 2007»
9 years 3 months ago
Random Subspace Two-Dimensional PCA for Face Recognition
The two-dimensional Principal Component Analysis (2DPCA) is a robust method in face recognition. Much recent research shows that the 2DPCA is more reliable than the well-known PCA ...
Nam Nguyen, Wanquan Liu, Svetha Venkatesh
AMFG
2005
IEEE
314views Biometrics» more  AMFG 2005»
9 years 2 months ago
Two-Dimensional Non-negative Matrix Factorization for Face Representation and Recognition
Non-negative matrix factorization (NMF) is a recently developed method for finding parts-based representation of non-negative data such as face images. Although it has successfully...
Daoqiang Zhang, Songcan Chen, Zhi-Hua Zhou
ISNN
2007
Springer
9 years 3 months ago
Two-Dimensional Bayesian Subspace Analysis for Face Recognition
Bayesian subspace analysis (BSA) has been successfully applied in data mining and pattern recognition. However, due to the use of probabilistic measure of similarity, it often need...
Daoqiang Zhang
IBPRIA
2007
Springer
9 years 3 months ago
False Positive Reduction in Breast Mass Detection Using Two-Dimensional PCA
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Arnau Oliver, Xavier Lladó, Joan Mart&iacut...
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