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» On Combining Classifiers
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ICCV
2009
IEEE
13 years 6 months ago
Group-sensitive multiple kernel learning for object categorization
In this paper, we propose a group-sensitive multiple kernel learning (GS-MKL) method to accommodate the intra-class diversity and the inter-class correlation for object categoriza...
Jingjing Yang, Yuanning Li, YongHong Tian, Lingyu ...
ICDE
2008
IEEE
171views Database» more  ICDE 2008»
14 years 10 months ago
Usage-Based Schema Matching
Existing techniques for schema matching are classified as either schema-based, instance-based, or a combination of both. In this paper, we define a new class of techniques, called ...
Hazem Elmeleegy, Mourad Ouzzani, Ahmed K. Elmagarm...
ICPR
2008
IEEE
14 years 10 months ago
Separability of ternary Error-Correcting Output Codes
Error Correcting Output Codes (ECOC) represent a successful framework to deal with multi-class categorization problems based on combining binary classifiers. In this paper, we pre...
Oriol Pujol, Petia Radeva, Sergio Escalera
PRL
1998
93views more  PRL 1998»
13 years 8 months ago
A connectionist method for pattern classification with diverse features
A novel connectionist method is proposed to simultaneously use diverse features in an optimal way for pattern classification. Unlike methods of combining multiple classifiers, a m...
Ke Chen 0001
ICCV
2009
IEEE
15 years 1 months ago
Super-Resolution from a Single Image
Methods for super-resolution can be broadly classified into two families of methods: (i) The classical multi-image super-resolution (combining images obtained at subpixel misali...
Daniel Glasner, Shai Bagon, Michal Irani