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» On Comparing Two Scenarios for Probabilistic Image Modelling
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RECOMB
2005
Springer
14 years 7 months ago
Learning Interpretable SVMs for Biological Sequence Classification
Background: Support Vector Machines (SVMs) ? using a variety of string kernels ? have been successfully applied to biological sequence classification problems. While SVMs achieve ...
Christin Schäfer, Gunnar Rätsch, Sö...
ECCV
2008
Springer
13 years 9 months ago
Unsupervised Classification and Part Localization by Consistency Amplification
We present a novel method for unsupervised classification, including the discovery of a new category and precise object and part localization. Given a set of unlabelled images, som...
Leonid Karlinsky, Michael Dinerstein, Dan Levi, Sh...
CORR
2010
Springer
210views Education» more  CORR 2010»
13 years 7 months ago
Exploiting Statistical Dependencies in Sparse Representations for Signal Recovery
Signal modeling lies at the core of numerous signal and image processing applications. A recent approach that has drawn considerable attention is sparse representation modeling, in...
Tomer Faktor, Yonina C. Eldar, Michael Elad
VISUALIZATION
2005
IEEE
14 years 29 days ago
Visualizing intersecting surfaces with nested-surface techniques
This paper describes the adaptation and evaluation of existing nestedsurface visualization techniques for the problem of displaying intersecting surfaces. For this work, we collab...
Chris Weigle, Russell M. Taylor II
FGR
2004
IEEE
170views Biometrics» more  FGR 2004»
13 years 11 months ago
3D Shape Constraint for Facial Feature Localization Using Probabilistic-like Output
This paper presents a method to automatically locate facial feature points under large variations in pose, illumination and facial expressions. First we propose a method to calcul...
Longbin Chen, Lei Zhang, HongJiang Zhang, Mohamed ...