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117
Voted
CVPR
2007
IEEE
16 years 3 months ago
2007
IEEE
Dimensionality reduction is an important issue when facing high-dimensional data. For supervised dimensionality reduction, Linear Discriminant Analysis (LDA) is one of the most po...
107
click to vote
CVPR
2008
IEEE
16 years 3 months ago
2008
IEEE
Even if the class label information is unknown, side information represents some equivalence constraints between pairs of patterns, indicating whether pairs originate from the sam...
122
Voted
CVPR
2008
IEEE
16 years 3 months ago
2008
IEEE
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
113
click to vote
CVPR
2008
IEEE
16 years 3 months ago
2008
IEEE
Over the years, many tensor based algorithms, e.g. two dimensional principle component analysis (2DPCA), two dimensional singular value decomposition (2DSVD), high order SVD, have...
106
Voted
ICCV
2003
IEEE
16 years 2 months ago
2003
IEEE
Learning visual models of object categories notoriously requires thousands of training examples; this is due to the diversity and richness of object appearance which requires mode...