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» Bayesian Learning of Sparse Classifiers
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CVPR
2007
IEEE
14 years 9 months ago
A boosting regression approach to medical anatomy detection
The state-of-the-art object detection algorithm learns a binary classifier to differentiate the foreground object from the background. Since the detection algorithm exhaustively s...
Shaohua Kevin Zhou, Jinghao Zhou, Dorin Comaniciu
ICASSP
2010
IEEE
13 years 8 months ago
Image-quality prediction of synthetic aperture sonar imagery
This work exploits several machine-learning techniques to address the problem of image-quality prediction of synthetic aperture sonar (SAS) imagery. The objective is to predict th...
David P. Williams
JMLR
2010
192views more  JMLR 2010»
13 years 2 months ago
Inducing Tree-Substitution Grammars
Inducing a grammar from text has proven to be a notoriously challenging learning task despite decades of research. The primary reason for its difficulty is that in order to induce...
Trevor Cohn, Phil Blunsom, Sharon Goldwater
KDD
2012
ACM
183views Data Mining» more  KDD 2012»
11 years 10 months ago
Mining discriminative components with low-rank and sparsity constraints for face recognition
This paper introduces a novel image decomposition approach for an ensemble of correlated images, using low-rank and sparsity constraints. Each image is decomposed as a combination...
Qiang Zhang, Baoxin Li
ICCV
2003
IEEE
14 years 9 months ago
Object Recognition with Informative Features and Linear Classification
In this paper we show that efficient object recognition can be obtained by combining informative features with linear classification. The results demonstrate the superiority of in...
Michel Vidal-Naquet, Shimon Ullman