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BMCBI
2006
74views more  BMCBI 2006»
15 years 7 months ago
An unsupervised classification scheme for improving predictions of prokaryotic TIS
Background: Although it is not difficult for state-of-the-art gene finders to identify coding regions in prokaryotic genomes, exact prediction of the corresponding translation ini...
Maike Tech, Peter Meinicke
BMCBI
2007
101views more  BMCBI 2007»
15 years 7 months ago
Robust detection and verification of linear relationships to generate metabolic networks using estimates of technical errors
Background: The size and magnitude of the metabolome, the ratio between individual metabolites and the response of metabolic networks is controlled by multiple cellular factors. A...
Frank Kose, Jan Budczies, Matthias Holschneider, O...
PRL
2008
152views more  PRL 2008»
15 years 7 months ago
WND-CHARM: Multi-purpose image classification using compound image transforms
We describe a multi-purpose image classifier that can be applied to a wide variety of image classification tasks without modifications or fine-tuning, and yet provide classificati...
Nikita Orlov, Lior Shamir, Tomasz J. Macura, Josia...
201
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CVPR
2005
IEEE
16 years 9 months ago
WaldBoost - Learning for Time Constrained Sequential Detection
: In many computer vision classification problems, both the error and time characterizes the quality of a decision. We show that such problems can be formalized in the framework of...
Jan Sochman, Jiri Matas
MA
2010
Springer
114views Communications» more  MA 2010»
15 years 5 months ago
Finite-sample inference with monotone incomplete multivariate normal data, II
We continue our recent work on finite-sample, i.e., non-asymptotic, inference with two-step, monotone incomplete data from Nd(µ, Σ), a multivariate normal population with mean ...
Wan-Ying Chang, Donald St. P. Richards