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» Feature selection for ranking using boosted trees
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DICTA
2003
15 years 1 months ago
Face Recognition Based on Multiple Region Features
For face recognition, face feature selection is an important step. Better features should result in better performance. This paper describes a robust face recognition algorithm usi...
Jiaming Li, Geoff Poulton, Ying Guo, Rong-yu Qiao
ISBI
2009
IEEE
15 years 6 months ago
Automatic Markup of Neural Cell Membranes Using Boosted Decision Stumps
To better understand the central nervous system, neurobiologists need to reconstruct the underlying neural circuitry from electron microscopy images. One of the necessary tasks is...
Kannan Umadevi Venkataraju, António R. C. P...
CVPR
2006
IEEE
16 years 1 months ago
BoostMotion: Boosting a Discriminative Similarity Function for Motion Estimation
Motion estimation for applications where appearance undergoes complex changes is challenging due to lack of an appropriate similarity function. In this paper, we propose to learn ...
Shaohua Kevin Zhou, Bogdan Georgescu, Dorin Comani...
MLDM
2007
Springer
15 years 5 months ago
Ensemble-based Feature Selection Criteria
Recursive Feature Elimination (RFE) combined with feature ranking is an effective technique for eliminating irrelevant features when the feature dimension is large, but it is diffi...
Terry Windeatt, Matthew Prior, Niv Effron, Nathan ...
PAMI
2008
175views more  PAMI 2008»
14 years 11 months ago
Discriminative Feature Co-Occurrence Selection for Object Detection
This paper describes an object detection framework that learns the discriminative co-occurrence of multiple features. Feature co-occurrences are automatically found by Sequential F...
Takeshi Mita, Toshimitsu Kaneko, Björn Stenge...