Linear discriminant analysis
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Many current face recognition algorithms perform badly when the lighting or pose of the probe and gallery images differ. In this… Expand Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The… Expand Linear dimensionality reduction methods, such as LDA, are often used in object recognition for feature extraction, but do not… Expand This paper proposes an innovative algorithm named 2D-LDA, which directly extracts the proper features from image matrices based… Expand Linear Discriminant Analysis (LDA) is a well-known scheme for feature extraction and dimension reduction. It has been used widely… Expand A non-linear classification technique based on Fisher's discriminant is proposed. The main ingredient is the kernel trick which… Expand Fisher-Rao linear discriminant analysis (LDA) is a valuable tool for multigroup classification. LDA is equivalent to maximum… Expand This paper describes the automatic selection of features from an image training set using the theories of multidimensional… Expand Fisher's linear discriminant analysis (LDA) is a popular data-analytic tool for studying the relationship between a set of… Expand With the availability of “canned” computer programs, it is extremely easy to run complex multivariate statistical analyses… Expand