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» Color Constancy Via Convex Kernel Optimization
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CVPR
2012
IEEE
11 years 10 months ago
Bag of textons for image segmentation via soft clustering and convex shift
We propose an unsupervised image segmentation method based on texton similarity and mode seeking. The input image is first convolved with a filter-bank, followed by soft cluster...
Zhiding Yu, Ang Li, Oscar C. Au, Chunjing Xu
IJCNN
2006
IEEE
14 years 1 months ago
Learning the Kernel in Mahalanobis One-Class Support Vector Machines
— In this paper, we show that one-class SVMs can also utilize data covariance in a robust manner to improve performance. Furthermore, by constraining the desired kernel function ...
Ivor W. Tsang, James T. Kwok, Shutao Li
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara
ICCV
2007
IEEE
14 years 9 months ago
Half Quadratic Analysis for Mean Shift: with Extension to A Sequential Data Mode-Seeking Method
Theoretical understanding and extension of mean shift procedure has received much attention recently [8, 18, 3]. In this paper, we present a theoretical exploration and an algorit...
Xiaotong Yuan, Stan Z. Li
TSP
2010
13 years 2 months ago
Code design for radar STAP via optimization theory
Abstract--In this paper, we deal with the problem of constrained code optimization for radar space-time adaptive processing (STAP) in the presence of colored Gaussian disturbance. ...
Antonio De Maio, Silvio De Nicola, Yongwei Huang, ...