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» Boosting Bayesian MAP Classification
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PAMI
2012
11 years 10 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...
ICIP
2010
IEEE
13 years 5 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»
13 years 7 months 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
14 years 2 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
PAMI
2008
153views more  PAMI 2008»
13 years 7 months 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