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» Learning Local Image Descriptors
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PASTE
2010
ACM
14 years 3 months ago
Learning universal probabilistic models for fault localization
Recently there has been significant interest in employing probabilistic techniques for fault localization. Using dynamic dependence information for multiple passing runs, learnin...
Min Feng, Rajiv Gupta
PRL
2008
147views more  PRL 2008»
13 years 9 months ago
Deformations, patches, and discriminative models for automatic annotation of medical radiographs
In this paper, we describe three different methods for the classification and annotation of medical radiographs. The methods were applied in the medical image annotation tasks of ...
Thomas Deselaers, Hermann Ney
SMI
2008
IEEE
181views Image Analysis» more  SMI 2008»
14 years 4 months ago
SHREC - 08 entry: Local 2D visual features for CAD Model retrieval
A local shape feature has an advantage in dealing with deformable or articulated 3D models. We evaluate the performance of our local, 2D visual features and their integration meth...
Kunio Osada, Takahiko Furuya, Ryutarou Ohbuchi
IJON
2011
169views more  IJON 2011»
13 years 5 months ago
Exploiting local structure in Boltzmann machines
Restricted Boltzmann Machines (RBM) are well-studied generative models. For image data, however, standard RBMs are suboptimal, since they do not exploit the local nature of image ...
Hannes Schulz, Andreas Müller 0004, Sven Behn...
ICPR
2006
IEEE
14 years 11 months ago
FAIR: Towards A New Feature for Affinely-Invariant Recognition
In this paper we propose the first version of FAIR, a low-dimensional image neighborhood descriptor that shows performance comparable to SIFT introduced by Lowe. The dimension of F...
Martin Matousek, Radim Sára