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» Boosting Object Detection Using Feature Selection
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WACV
2002
IEEE
14 years 8 days ago
Boosting Image Orientation Detection with Indoor vs. Outdoor Classification
Automatic detection of image orientation is a very important operation in photo image management. In this paper, we propose an automated method based on the boosting algorithm to ...
Lei Zhang, Mingjing Li, HongJiang Zhang
NIPS
2003
13 years 8 months ago
Mutual Boosting for Contextual Inference
Mutual Boosting is a method aimed at incorporating contextual information to augment object detection. When multiple detectors of objects and parts are trained in parallel using A...
Michael Fink 0002, Pietro Perona
ICRA
2008
IEEE
170views Robotics» more  ICRA 2008»
14 years 1 months ago
Human detection using iterative feature selection and logistic principal component analysis
— We present a fast feature selection algorithm suitable for object detection applications where the image being tested must be scanned repeatedly to detected the object of inter...
Wael Abd-Almageed, Larry S. Davis
IWBRS
2005
Springer
168views Biometrics» more  IWBRS 2005»
14 years 26 days ago
Gabor Feature Selection for Face Recognition Using Improved AdaBoost Learning
Though AdaBoost has been widely used for feature selection and classifier learning, many of the selected features, or weak classifiers, are redundant. By incorporating mutual infor...
LinLin Shen, Li Bai, Daniel Bardsley, Yangsheng Wa...
CIVR
2008
Springer
279views Image Analysis» more  CIVR 2008»
13 years 9 months ago
Semi-supervised learning of object categories from paired local features
This paper presents a semi-supervised learning (SSL) approach to find similarities of images using statistics of local matches. SSL algorithms are well known for leveraging a larg...
Wen Wu, Jie Yang