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ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
14 years 10 months ago
Similarity Functions for Categorization: from Monolithic to Category Specific
Similarity metrics that are learned from labeled training data can be advantageous in terms of performance and/or efficiency. These learned metrics can then be used in conjuncti...
Boris Babenko, Steve Branson, Serge Belongie
CVPR
2006
IEEE
14 years 7 months ago
A Design Principle for Coarse-to-Fine Classification
Coarse-to-fine classification is an efficient way of organizing object recognition in order to accommodate a large number of possible hypotheses and to systematically exploit shar...
Sachin Gangaputra, Donald Geman
CVPR
2006
IEEE
14 years 7 months ago
Accelerated Kernel Feature Analysis
A fast algorithm, Accelerated Kernel Feature Analysis (AKFA), that discovers salient features evidenced in a sample of n unclassified patterns, is presented. Like earlier kernel-b...
Xianhua Jiang, Yuichi Motai, Robert R. Snapp, Xing...
TRS
2008
13 years 5 months ago
The Neurophysiological Bases of Cognitive Computation Using Rough Set Theory
A popular view is that the brain works in a similar way to a digital computer or a Universal Turing Machine by processing symbols. Psychophysical experiments and our amazing capabi...
Andrzej W. Przybyszewski
ICCV
2007
IEEE
14 years 7 months ago
Spherical-Homoscedastic Shapes
Shape analysis requires invariance under translation, scale and rotation. Translation and scale invariance can be realized by normalizing shape vectors with respect to their mean ...
Onur C. Hamsici, Aleix M. Martínez