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ICCV
2009
IEEE
16 years 3 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...
CIARP
2007
Springer
15 years 4 months ago
Multi-class Binary Object Categorization Using Blurred Shape Models
The main difficulty in the binary object classification field lays in dealing with a high variability of symbol appearance. Rotation, partial occlusions, elastic deformations, or...
Sergio Escalera, Alicia Fornés, Oriol Pujol...
PAMI
2010
170views more  PAMI 2010»
14 years 9 months ago
On the Decoding Process in Ternary Error-Correcting Output Codes
—A common way to model multiclass classification problems is to design a set of binary classifiers and to combine them. Error-Correcting Output Codes (ECOC) represent a successfu...
Sergio Escalera, Oriol Pujol, Petia Radeva
DRR
2009
14 years 8 months ago
Using synthetic data safely in classification
When is it safe to use synthetic data in supervised classification? Trainable classifier technologies require large representative training sets consisting of samples labeled with...
Jean Nonnemaker, Henry Baird
70
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CIKM
2008
Springer
15 years 14 days ago
Error-driven generalist+experts (edge): a multi-stage ensemble framework for text categorization
We introduce a multi-stage ensemble framework, ErrorDriven Generalist+Expert or Edge, for improved classification on large-scale text categorization problems. Edge first trains a ...
Jian Huang 0002, Omid Madani, C. Lee Giles