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» Optimizing Learning in Image Retrieval
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CLOR
2006
14 years 1 months ago
A Sparse Object Category Model for Efficient Learning and Complete Recognition
We present a "parts and structure" model for object category recognition that can be learnt efficiently and in a weakly-supervised manner: the model is learnt from examp...
Robert Fergus, Pietro Perona, Andrew Zisserman
AAAI
1996
13 years 11 months ago
A Hybrid Learning Approach for Better Recognition of Visual Objects
Real world images often contain similar objects but with different rotations, noise, or other visual alterations. Vision systems should be able to recognize objects regardless of ...
Ibrahim F. Imam, Srinivas Gutta
ECCV
2006
Springer
15 years 2 days ago
Learning Compositional Categorization Models
Abstract. This contribution proposes a compositional approach to visual object categorization of scenes. Compositions are learned from the Caltech 101 database1 intermediate abstra...
Björn Ommer, Joachim M. Buhmann
ICIP
2003
IEEE
14 years 11 months ago
Inverse halftoning by decision tree learning
Inverse halftoning is the process to retrieve a (gray) continuous-tone image from a halftone. Recently, machinelearning-based inverse halftoning techniques have been proposed. Dec...
Hae Yong Kim, Ricardo L. de Queiroz
NIPS
2008
13 years 11 months ago
Unsupervised Learning of Visual Sense Models for Polysemous Words
Polysemy is a problem for methods that exploit image search engines to build object category models. Existing unsupervised approaches do not take word sense into consideration. We...
Kate Saenko, Trevor Darrell