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» Feature selection in a kernel space
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ICIP
2007
IEEE
14 years 9 months ago
Iterative Feature Selection for Color Texture Classification
In this paper, we describe a new approach for color texture classification by use of Haralick features extracted from color co-occurrence matrices. As the color of each pixel can ...
Alice Porebski, Nicolas Vandenbroucke, Ludovic Mac...
MODELS
2009
Springer
14 years 2 months ago
Dead or Alive: finding zombie features in the Linux kernel
Variability management in operating systems is an errorprone and tedious task. This is especially true for the Linux operating system, which provides a specialized tool called Kco...
Reinhard Tartler, Julio Sincero, Wolfgang Schr&oum...
CVPR
2007
IEEE
14 years 9 months ago
Object Tracking by Asymmetric Kernel Mean Shift with Automatic Scale and Orientation Selection
Tracking objects using the mean shift method is performed by iteratively translating a kernel in the image space such that the past and current object observations are similar. Tr...
Alper Yilmaz
ICML
2004
IEEE
14 years 8 months ago
Robust feature induction for support vector machines
The goal of feature induction is to automatically create nonlinear combinations of existing features as additional input features to improve classification accuracy. Typically, no...
Rong Jin, Huan Liu
ICML
2008
IEEE
14 years 8 months ago
A reproducing kernel Hilbert space framework for pairwise time series distances
A good distance measure for time series needs to properly incorporate the temporal structure, and should be applicable to sequences with unequal lengths. In this paper, we propose...
Zhengdong Lu, Todd K. Leen, Yonghong Huang, Deniz ...