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ECCV
2004
Springer
14 years 7 months ago
Dimensionality Reduction by Canonical Contextual Correlation Projections
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...
Marco Loog, Bram van Ginneken, Robert P. W. Duin
ICIC
2009
Springer
13 years 10 months ago
Dimension Reduction Using Semi-Supervised Locally Linear Embedding for Plant Leaf Classification
Plant has plenty use in foodstuff, medicine and industry, and is also vitally important for environmental protection. So, it is important and urgent to recognize and classify plant...
Shanwen Zhang, Kwok-Wing Chau
BMCBI
2010
243views more  BMCBI 2010»
13 years 5 months ago
Comparative study of unsupervised dimension reduction techniques for the visualization of microarray gene expression data
Background: Visualization of DNA microarray data in two or three dimensional spaces is an important exploratory analysis step in order to detect quality issues or to generate new ...
Christoph Bartenhagen, Hans-Ulrich Klein, Christia...
ECCV
2004
Springer
14 years 7 months ago
Transformation-Invariant Embedding for Image Analysis
Abstract. Dimensionality reduction is an essential aspect of visual processing. Traditionally, linear dimensionality reduction techniques such as principle components analysis have...
Ali Ghodsi, Jiayuan Huang, Dale Schuurmans
ISVC
2010
Springer
13 years 3 months ago
Combining Automated and Interactive Visual Analysis of Biomechanical Motion Data
Abstract. We present a framework for combining automated and interactive visual analysis techniques for use on high-resolution biomechanical data. Analyzing the complex 3D motion o...
Scott Spurlock, Remco Chang, Xiaoyu Wang, George A...