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» Subspace Analysis Using Random Mixture Models
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ECCV
2002
Springer
14 years 9 months ago
Robust Parameterized Component Analysis
Principal ComponentAnalysis (PCA) has been successfully applied to construct linear models of shape, graylevel, and motion. In particular, PCA has been widely used to model the var...
Fernando De la Torre, Michael J. Black
CIVR
2007
Springer
139views Image Analysis» more  CIVR 2007»
14 years 1 months ago
Video search in concept subspace: a text-like paradigm
Though both quantity and quality of semantic concept detection in video are continuously improving, it still remains unclear how to exploit these detected concepts as semantic ind...
Xirong Li, Dong Wang, Jianmin Li, Bo Zhang
ICASSP
2008
IEEE
14 years 1 months ago
A weighted subspace approach for improving bagging performance
Bagging is an ensemble method that uses random resampling of a dataset to construct models. In classification scenarios, the random resampling procedure in bagging induces some c...
Qu-Tang Cai, Chun-Yi Peng, Chang-Shui Zhang
EVOW
2008
Springer
13 years 9 months ago
A Hybrid Random Subspace Classifier Fusion Approach for Protein Mass Spectra Classification
Classifier fusion strategies have shown great potential to enhance the performance of pattern recognition systems. There is an agreement among researchers in classifier combination...
Amin Assareh, Mohammad Hassan Moradi, L. Gwenn Vol...
ICASSP
2011
IEEE
12 years 11 months ago
A partial least squares framework for speaker recognition
Modern approaches to speaker recognition (verification) operate in a space of “supervectors” created via concatenation of the mean vectors of a Gaussian mixture model (GMM) a...
Balaji Vasan Srinivasan, Dmitry N. Zotkin, Ramani ...