High-dimensional data such as hyperspectral imagery is traditionally acquired in full dimensionality before being reduced in dimension prior to processing. Conventional dimensiona...
James E. Fowler, Qian Du, Wei Zhu, Nicolas H. Youn...
A linear, discriminative, supervised technique for reducing feature vectors extracted from image data to a lower-dimensional representation is proposed. It is derived from classica...
Recently the problem of dimensionality reduction (or, subspace learning) has received a lot of interests in many fields of information processing, including data mining, informati...
We consider the problem of document indexing and representation. Recently, Locality Preserving Indexing (LPI) was proposed for learning a compact document subspace. Different from...
5th International Symposium on Visual Computing, Las Vegas, Nevada, USA, Nov 30 - Dec 2, 2009 The Laplacian pyramid recursively splits an image into local averages and local diff...