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» Combining SVM Classifiers for Multiclass Problem: Its Applic...
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PR
2006
229views more  PR 2006»
13 years 7 months ago
FS_SFS: A novel feature selection method for support vector machines
In many pattern recognition applications, high-dimensional feature vectors impose a high computational cost as well as the risk of "overfitting". Feature Selection addre...
Yi Liu, Yuan F. Zheng
ICPR
2008
IEEE
14 years 8 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
BMCBI
2010
224views more  BMCBI 2010»
13 years 7 months ago
An adaptive optimal ensemble classifier via bagging and rank aggregation with applications to high dimensional data
Background: Generally speaking, different classifiers tend to work well for certain types of data and conversely, it is usually not known a priori which algorithm will be optimal ...
Susmita Datta, Vasyl Pihur, Somnath Datta
ICCV
2009
IEEE
15 years 13 days ago
Weakly supervised discriminative localization and classification: a joint learning process
Visual categorization problems, such as object classification or action recognition, are increasingly often approached using a detection strategy: a classifier function is first ...
Minh Hoai Nguyen, Lorenzo Torresani, Fernando de l...
COST
2009
Springer
172views Multimedia» more  COST 2009»
13 years 5 months ago
Facial Expression Recognition Using Two-Class Discriminant Features
This paper presents a novel facial expression recognition methodology. In order to classify the expression of a test face to one of seven pre-determined facial expression classes, ...
Marios Kyperountas, Ioannis Pitas