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ICDAR
2003
IEEE
14 years 24 days ago
Character Recognition by Adaptive Statistical Similarity
Handwriting recognition and OCR systems need to cope with a wide variety of writing styles and fonts, many of them possibly not previously encountered during training. This paper d...
Thomas M. Breuel
ICCV
2009
IEEE
1019views Computer Vision» more  ICCV 2009»
15 years 14 days 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
ECCV
2008
Springer
14 years 9 months ago
Multiple Component Learning for Object Detection
Abstract. Object detection is one of the key problems in computer vision. In the last decade, discriminative learning approaches have proven effective in detecting rigid objects, a...
Boris Babenko, Pietro Perona, Piotr Dollár,...
CVPR
2008
IEEE
13 years 9 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
CVPR
2007
IEEE
14 years 9 months ago
Using Segmentation to Verify Object Hypotheses
We present an approach for object recognition that combines detection and segmentation within a efficient hypothesize/test framework. Scanning-window template classifiers are the ...
Deva Ramanan