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ECCV
2004
Springer
14 years 9 months ago
2004
Springer
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
CAV
1999
Springer
13 years 12 months ago
1999
Springer
Of special interest in formal verification are safety properties, which assert that the system always stays within some allowed region. A computation that violates a general linea...
ICPR
2002
IEEE
14 years 8 months ago
2002
IEEE
Manifold Pursuit (MP) extends Principal Component Analysis to be invariant to a desired group of image-plane transformations of an ensemble of un-aligned images. We derive a simpl...
TIP
1998
13 years 7 months ago
1998
Abstract—We propose a method for the reconstruction of signals and images observed partially through a linear operator with a large support (e.g., a Fourier transform on a sparse...
CORR
2010
Springer
13 years 7 months ago
2010
Springer
Abstract: The Principal Component Analysis (PCA) is a data dimensionality reduction technique well-suited for processing data from sensor networks. It can be applied to tasks like ...