Learning Pattern Transformation Manifolds with Parametric Atom Selection

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2011-05-02

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Vural, Elif

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https://hdl.handle.net/11511/76770

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Learning pattern transformation manifolds for classification Vural, Elif (2013-02-21) Manifold models provide low-dimensional representations that are useful for analyzing and classifying data in a transformation-invariant way. In this paper we study the problem of jointly building multiple pattern transformation manifolds from a collection of image sets, where each set consists of observations from a class of geometrically transformed signals. We build the manifolds such that each manifold approximates a different signal class. Each manifold is characterized by a representative pattern that...
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Citation Formats

E. Vural, “Learning Pattern Transformation Manifolds with Parametric Atom Selection,” 2011, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/76770.