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AAAI
2011
12 years 10 months ago
Improving Semi-Supervised Support Vector Machines Through Unlabeled Instances Selection
Semi-supervised support vector machines (S3VMs) are a kind of popular approaches which try to improve learning performance by exploiting unlabeled data. Though S3VMs have been fou...
Yu-Feng Li, Zhi-Hua Zhou
EVOW
2007
Springer
14 years 2 months ago
Classification of Cell Fates with Support Vector Machine Learning
In human mesenchymal stem cells the envelope surrounding the nucleus, as visualized by the nuclear lamina, has a round and flat shape. The lamina structure is considerably deformed...
Ofer M. Shir, Vered Raz, Roeland W. Dirks, Thomas ...
ISBI
2004
IEEE
14 years 10 months ago
Morphological Classification of Medical Images using Nonlinear Support Vector Machines
The wavelet decomposition of a high-dimensional shape transformation posed in a mass-preserving framework is used as a morphological signature of a brain image. Population differe...
Christos Davatzikos, Dinggang Shen, Zhiqiang Lao, ...
FGR
2008
IEEE
240views Biometrics» more  FGR 2008»
14 years 4 months ago
Face recognition and alignment using support vector machines
Face recognition in the presence of pose changes remains a largely unsolved problem. Severe pose changes, resulting in dramatically different appearances, is one of the main dif...
Antony Lam, Christian R. Shelton
ICIC
2007
Springer
14 years 4 months ago
Fuzzy Modeling Via On-Line Clustering and Support Vector Machine
Abstract. This paper describes a novel fuzzy rule-based modeling approach for some slow industrial processses. Structure identification is realized by clustering and support vecto...
Julio César Tovar, Wen Yu, Xiaoou Li