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Institute of Technology Dimensionality Reduction for Multispectral Skin Data
 

Summary: STEVENS
Institute of Technology
Dimensionality Reduction for Multispectral Skin Data
Dongmei Shi Elli Angelopoulou
Department of Computer Science
Stevens Institute of Technology
Hoboken, NJ, 07030, USA
dshi1|elli@cs.stevens-tech.edu
Department of Computer Science
Technical Report CS-2004-9
Department of Computer Science · Stevens Institute of Technology
Castle Point on Hudson · Hoboken, NJ 07030 · USA
Dimensionality Reduction for Multispectral Skin Data
Dongmei Shi Elli Angelopoulou
Abstract
Principal Component Analysis ( PCA ), Locally Linear Embedding ( LLE ) and
Isomap techniques can be used to process and analyze high-dimensional data domains.
These methodologies create low-dimensional embeddings of the original data which are
easier to work with than the initial high-dimensional data. The goal of this report is
to show how the above methods can be applied to very high-dimensional skin data

  

Source: Angelopoulou, Elli - Department of Computer Science, Friedrich Alexander University Erlangen Nürnberg

 

Collections: Computer Technologies and Information Sciences