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» Learning Boosted Asymmetric Classifiers for Object Detection
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WWW
2008
ACM
14 years 8 months ago
Floatcascade learning for fast imbalanced web mining
This paper is concerned with the problem of Imbalanced Classification (IC) in web mining, which often arises on the web due to the "Matthew Effect". As web IC applicatio...
Xiaoxun Zhang, Xueying Wang, Honglei Guo, Zhili Gu...
CVPR
2007
IEEE
14 years 9 months ago
Joint Optimization of Cascaded Classifiers for Computer Aided Detection
The existing methods for offline training of cascade classifiers take a greedy search to optimize individual classifiers in the cascade, leading inefficient overall performance. W...
Murat Dundar, Jinbo Bi
ICCV
2005
IEEE
14 years 9 months ago
A Supervised Learning Framework for Generic Object Detection in Images
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
Saad Ali, Mubarak Shah
DAGM
2003
Springer
14 years 21 days ago
Empirical Analysis of Detection Cascades of Boosted Classifiers for Rapid Object Detection
Recently Viola et al. have introduced a rapid object detection scheme based on a boosted cascade of simple feature classifiers. In this paper we introduce and empirically analysis ...
Rainer Lienhart, Alexander Kuranov, Vadim Pisarevs...
CVPR
2008
IEEE
13 years 9 months ago
Optimizing discrimination-efficiency tradeoff in integrating heterogeneous local features for object detection
A large variety of image features has been invented for detection of objects of a known class. We propose a framework to optimize the discrimination-efficiency tradeoff in integra...
Bo Wu, Ram Nevatia