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» Class Separability in Spaces Reduced By Feature Selection
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CVPR
2008
IEEE
13 years 10 months ago
Classification via semi-Riemannian spaces
In this paper, we develop a geometric framework for linear or nonlinear discriminant subspace learning and classification. In our framework, the structures of classes are conceptu...
Deli Zhao, Zhouchen Lin, Xiaoou Tang
DEXAW
2007
IEEE
157views Database» more  DEXAW 2007»
14 years 17 days ago
Dimensionality Reduction in a P2P System
Peers and data objects in the Hybrid Overlay Network (HON) are organized in a ndimensional feature space. As the dimensionality increases, peers and data objects become sparse and ...
Mouna Kacimi, Kokou Yétongnon
TSMC
1998
93views more  TSMC 1998»
13 years 8 months ago
Toward a completely automatic neural-network-based human chromosome analysis
Abstract—The application of neural networks (NN’s) to automatic analysis of chromosome images is investigated in this paper. All aspects of the analysis, namely segmentation, f...
Boaz Lerner
ICIP
2006
IEEE
14 years 10 months ago
Modulation Domain Features for Discriminating Infrared Targets and Backgrounds
For the first time, we compute modulation domain features for infrared targets and backgrounds, including dominant modulations that characterize the local texture contrast, orient...
Chuong T. Nguyen, Joseph P. Havlicek
ICPR
2008
IEEE
14 years 3 months ago
Computer graphics identification using genetic algorithm
This paper proposes the use of genetic algorithm to select an optimal feature set for distinguishing computer graphics from digital photographic images. Our previously developed a...
Wen Chen, Yun Q. Shi, Guorong Xuan, Wei Su