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TRECVID
2008
9 years 9 months ago
National Institute of Informatics, Japan at TRECVID 2008
This paper reports our experiments for TRECVID 2008 tasks: high level feature extraction, search and contentbased copy detection. For the high level feature extraction task, we use...
Duy-Dinh Le, Xiaomeng Wu, Shin'ichi Satoh, Sheetal...
FSKD
2006
Springer
147views Fuzzy Logic» more  FSKD 2006»
9 years 11 months ago
Adaptive Nearest Neighbor Classifier Based on Supervised Ellipsoid Clustering
Nearest neighbor classifier is a widely-used effective method for multi-class problems. However, it suffers from the problem of the curse of dimensionality in high dimensional spac...
Guo-Jun Zhang, Ji-Xiang Du, De-Shuang Huang, Tat-M...
ICPR
2004
IEEE
10 years 9 months ago
Direct Condensing: An Efficient Voronoi Condensing Algorithm for Nearest Neighbor Classifiers
Voronoi condensing reduces training patterns of nearest neighbor classifiers without changing the classification boundaries. This method plays important roles not only in the near...
Takekazu Kato, Toshikazu Wada
CVPR
2008
IEEE
10 years 10 months ago
Beyond sliding windows: Object localization by efficient subwindow search
Most successful object recognition systems rely on binary classification, deciding only if an object is present or not, but not providing information on the actual object location...
Christoph H. Lampert, Matthew B. Blaschko, Thomas ...
CVPR
2006
IEEE
10 years 10 months ago
SVM-KNN: Discriminative Nearest Neighbor Classification for Visual Category Recognition
We consider visual category recognition in the framework of measuring similarities, or equivalently perceptual distances, to prototype examples of categories. This approach is qui...
Alexander C. Berg, Hao Zhang 0003, Jitendra Malik,...
CVPR
2005
IEEE
10 years 10 months ago
Random Subspaces and Subsampling for 2-D Face Recognition
Random subspaces are a popular ensemble construction technique that improves the accuracy of weak classifiers. It has been shown, in different domains, that random subspaces combi...
Nitesh V. Chawla, Kevin W. Bowyer
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