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 ...
In this paper a novel method called Extended TwoDimensional PCA (E2DPCA) is proposed which is an extension to the original 2DPCA. We state that the covariance matrix of 2DPCA is e...
Mehran Safayani, Mohammad Taghi Manzuri Shalmani, ...
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...
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...
In [1], three popular subspace face recognition methods, PCA, Bayes, and LDA were analyzed under the same framework and an unified subspace analysis was proposed. However, since t...