7536 search results - page 78 / 1508 » Localized Components Analysis |
139
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ECCV
2002
Springer
16 years 6 months ago
2002
Springer
Abstract. Principal Component Analysis (PCA) is one of the most popular techniques for dimensionality reduction of multivariate data points with application areas covering many bra...
160
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ICIP
2006
IEEE
16 years 6 months ago
2006
IEEE
Linear techniques are widely used to reduce the dimension of image representation spaces in applications such as image indexing and object recognition. Optimal Component Analysis ...
138
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ICIP
2002
IEEE
16 years 6 months ago
2002
IEEE
We present a hybrid and parallel system based on artificial neural networks for a face invariant classifier and general pattern recognition problems. A set of face features is ext...
156
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ICML
2007
IEEE
16 years 5 months ago
2007
IEEE
Given a sample covariance matrix, we examine the problem of maximizing the variance explained by a particular linear combination of the input variables while constraining the numb...
147
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ICML
2006
IEEE
16 years 5 months ago
2006
IEEE
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...