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» Feature selection for linear support vector machines
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TMM
2002
123views more  TMM 2002»
13 years 7 months ago
Object tracking using the Gabor wavelet transform and the golden section algorithm
This paper presents an object tracking method for object-based video processing which uses a two-dimensional (2-D) Gabor wavelet transform (GWT) and a 2-D golden section algorithm....
Chao He, Yuan F. Zheng, Stanley C. Ahalt
ESANN
2004
13 years 9 months ago
Fuzzy LP-SVMs for Multiclass Problems
Abstract. In this paper, we propose fuzzy linear programming support vector machines (LP-SVMs) that resolve unclassifiable regions for multiclass problems. Namely, in the direction...
Shigeo Abe
ISBI
2011
IEEE
12 years 11 months ago
Network cycle features: Application to computer-aided Gleason grading of prostate cancer histopathological images
Features extracted from cell networks have become popular tools in histological image analysis. However, existing features do not take sufficient advantage of the cycle structure...
Parmeshwar Khurd, Leo Grady, Ali Kamen, Summer Gib...
VLSISP
2010
254views more  VLSISP 2010»
13 years 6 months ago
Manifold Based Local Classifiers: Linear and Nonlinear Approaches
Abstract In case of insufficient data samples in highdimensional classification problems, sparse scatters of samples tend to have many ‘holes’—regions that have few or no nea...
Hakan Cevikalp, Diane Larlus, Marian Neamtu, Bill ...
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 2 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...