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» Boosting Bayesian MAP Classification
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143
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PAMI
2012
13 years 2 months ago
Trainable Convolution Filters and Their Application to Face Recognition
—In this paper, we present a novel image classification system that is built around a core of trainable filter ensembles that we call Volterra kernel classifiers. Our system trea...
Ritwik Kumar, Arunava Banerjee, Baba C. Vemuri, Ha...
120
Voted
ICIP
2010
IEEE
14 years 10 months ago
Combining free energy score spaces with information theoretic kernels: Application to scene classification
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
Manuele Bicego, Alessandro Perina, Vittorio Murino...
BMCBI
2006
223views more  BMCBI 2006»
15 years 12 days ago
PSMIX: an R package for population structure inference via maximum likelihood method
Background: Inference of population stratification and individual admixture from genetic markers is an integrative part of a study in diverse situations, such as association mappi...
Baolin Wu, Nianjun Liu, Hongyu Zhao
ICIP
2008
IEEE
15 years 6 months ago
Correlation Embedding Analysis
—Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms usi...
Yun Fu, Thomas S. Huang
80
Voted
PAMI
2008
153views more  PAMI 2008»
15 years 9 days ago
Correlation Metric for Generalized Feature Extraction
Beyond conventional linear and kernel-based feature extraction, we present a more generalized formulation for feature extraction in this paper. Two representative algorithms using ...
Yun Fu, Shuicheng Yan, Thomas S. Huang