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» Co-Tracking Using Semi-Supervised Support Vector Machines
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IWANN
2009
Springer
15 years 9 months ago
Feature Selection in Survival Least Squares Support Vector Machines with Maximal Variation Constraints
This work proposes the use of maximal variation analysis for feature selection within least squares support vector machines for survival analysis. Instead of selecting a subset of ...
Vanya Van Belle, Kristiaan Pelckmans, Johan A. K. ...
ICMCS
2006
IEEE
177views Multimedia» more  ICMCS 2006»
15 years 8 months ago
Mixed Type Audio Classification with Support Vector Machine
Content-based classification of audio data is an important problem for various applications such as overall analysis of audio-visual streams, boundary detection of video story se...
Lei Chen 0002, Sule Gündüz, M. Tamer &Ou...
ISSRE
2005
IEEE
15 years 8 months ago
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
The software development process imposes major impacts on the quality of software at every development stage; therefore, a common goal of each software development phase concerns ...
Fei Xing, Ping Guo, Michael R. Lyu
135
Voted
CVBIA
2005
Springer
15 years 8 months ago
Segmenting Brain Tumors with Conditional Random Fields and Support Vector Machines
Abstract. Markov Random Fields (MRFs) are a popular and wellmotivated model for many medical image processing tasks such as segmentation. Discriminative Random Fields (DRFs), a dis...
Chi-Hoon Lee, Mark Schmidt, Albert Murtha, Aalo Bi...
116
Voted
ISBI
2008
IEEE
16 years 3 months ago
Support vector machine for data on manifolds: An application to image analysis
The Support Vector Machine (SVM) is a powerful tool for classification. We generalize SVM to work with data objects that are naturally understood to be lying on curved manifolds, ...
Suman K. Sen, Mark Foskey, James Stephen Marron, M...