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» On Feature Extraction via Kernels
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TKDE
2011
479views more  TKDE 2011»
13 years 4 months ago
Learning Semi-Riemannian Metrics for Semisupervised Feature Extraction
—Discriminant feature extraction plays a central role in pattern recognition and classification. Linear Discriminant Analysis (LDA) is a traditional algorithm for supervised feat...
Wei Zhang, Zhouchen Lin, Xiaoou Tang
ICPR
2010
IEEE
14 years 1 months ago
Monogenic Binary Pattern (MBP): A Novel Feature Extraction and Representation Model for Face Recognition
A novel feature extraction method, namely monogenic binary pattern (MBP), is proposed in this paper based on the theory of monogenic signal analysis, and the histogram of MBP (HMB...
Meng Yang, Lei Zhang, Lin Zhang, David Zhang
ICIP
2009
IEEE
14 years 11 months ago
Spatio-temporal Tube Kernel For Actor Retrieval
This paper presents an actor video retrieval system based on face video-tubes extraction and representation with sets of temporally coherent features. Visual features, SIFT points...
VAMOS
2010
Springer
13 years 7 months ago
The Variability Model of The Linux Kernel
Lack of realistic benchmarks hinders efficient design and evaluation of analysis techniques for feature models. We extract a variability model from the code base of the Linux kerne...
Steven She, Rafael Lotufo, Thorsten Berger, Andrze...
AAAI
2010
13 years 11 months ago
Stability and Incentive Compatibility in a Kernel-Based Combinatorial Auction
We present the design and analysis of an approximately incentive-compatible combinatorial auction. In just a single run, the auction is able to extract enough value information fr...
Sébastien Lahaie