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» Learning and using taxonomies for fast visual categorization
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CVPR
2008
IEEE
14 years 6 months ago
Learning and using taxonomies for fast visual categorization
The computational complexity of current visual categorization algorithms scales linearly at best with the number of categories. The goal of classifying simultaneously Ncat = 104 -...
Gregory Griffin, Darya Perona
ICCV
2005
IEEE
13 years 10 months ago
Object Categorization by Learned Universal Visual Dictionary
This paper presents a new algorithm for the automatic recognition of object classes from images (categorization). Compact and yet discriminative appearance-based object class mode...
John M. Winn, Antonio Criminisi, Thomas P. Minka
WWW
2004
ACM
14 years 5 months ago
Web taxonomy integration using support vector machines
We address the problem of integrating objects from a source taxonomy into a master taxonomy. This problem is not only currently pervasive on the web, but also important to the eme...
Dell Zhang, Wee Sun Lee
CVPR
2007
IEEE
14 years 6 months ago
Discovery of Collocation Patterns: from Visual Words to Visual Phrases
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...
Junsong Yuan, Ying Wu, Ming Yang
SBRN
2008
IEEE
13 years 11 months ago
Multi-label Text Categorization Using VG-RAM Weightless Neural Networks
In automated multi-label text categorization, an automatic categorization system should output a category set, whose size is unknown a priori, for each document under analysis. Ma...
Claudine Badue, Felipe Pedroni, Alberto Ferreira d...