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AAAI
2011
14 years 2 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
15 years 6 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 ...
144
Voted
ISBI
2004
IEEE
16 years 3 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, ...
125
Voted
FGR
2008
IEEE
240views Biometrics» more  FGR 2008»
15 years 9 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
15 years 8 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