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» Evolving kernels for support vector machine classification
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FSS
2007
102views more  FSS 2007»
15 years 4 months ago
Extraction of fuzzy rules from support vector machines
The relationship between support vector machines (SVMs) and Takagi–Sugeno–Kang (TSK) fuzzy systems is shown. An exact representation of SVMs as TSK fuzzy systems is given for ...
Juan Luis Castro, L. D. Flores-Hidalgo, Carlos Jav...
ICML
2008
IEEE
16 years 5 months ago
Stopping conditions for exact computation of leave-one-out error in support vector machines
We propose a new stopping condition for a Support Vector Machine (SVM) solver which precisely reflects the objective of the Leave-OneOut error computation. The stopping condition ...
Klaus-Robert Müller, Pavel Laskov, Vojtech Fr...
ICIP
2006
IEEE
16 years 6 months ago
Support Vector Machines for Camera Calibration Problem
This paper presents a statistical learning-based solution to the camera calibration problem in which the Support Vector Machines (SVM) are used for the estimation of the projectio...
Refaat M. Mohamed, Abdelrehim H. Ahmed, Ahmed Eid,...
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ICASSP
2008
IEEE
15 years 11 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
NIPS
2003
15 years 5 months ago
Phonetic Speaker Recognition with Support Vector Machines
A recent area of significant progress in speaker recognition is the use of high level features—idiolect, phonetic relations, prosody, discourse structure, etc. A speaker not on...
William M. Campbell, Joseph P. Campbell, Douglas A...