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» Optimal feature selection for support vector machines
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ICPR
2010
IEEE
14 years 2 months ago
Exploiting Visual Quasi-Periodicity for Automated Chewing Event Detection Using Active Appearance Models and Support Vector Mach
We present a method that automatically detects chewing events in surveillance video of a subject. Firstly, an Active Appearance Model (AAM) is used to track a subject’s face acr...
Steven Cadavid, Mohamed Abdel-Mottaleb
CVBIA
2005
Springer
14 years 1 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...
CVPR
2004
IEEE
13 years 11 months ago
Learning in Region-Based Image Retrieval with Generalized Support Vector Machines
Relevance feedback approaches based on support vector machine (SVM) learning have been applied to significantly improve retrieval performance in content-based image retrieval (CBI...
Iker Gondra, Douglas R. Heisterkamp
JRTIP
2008
151views more  JRTIP 2008»
13 years 6 months ago
Automatic gender recognition based on pixel-pattern-based texture feature
A pixel-pattern-based texture feature (PPBTF) is proposed for real-time gender recognition. A gray-scale image is transformed into a pattern map where edges and lines are to be use...
Huchuan Lu, Yingjie Huang, Yen-Wei Chen, Deli Yang
FGR
2004
IEEE
130views Biometrics» more  FGR 2004»
13 years 11 months ago
Sparse Models for Gender Classification
A class of sparse regularization functions are considered for the developing sparse classifiers for determining facial gender. The sparse classification method aims to both select...
Nicholas Costen, Martin Brown, Shigeru Akamatsu