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» Support Vector Classification with Input Data Uncertainty
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108
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NN
2000
Springer
161views Neural Networks» more  NN 2000»
15 years 5 days ago
How good are support vector machines?
Support vector (SV) machines are useful tools to classify populations characterized by abrupt decreases in density functions. At least for one class of Gaussian data model the SV ...
Sarunas Raudys
101
Voted
PAMI
2008
302views more  PAMI 2008»
15 years 10 days ago
Learning to Detect Moving Shadows in Dynamic Environments
We propose a novel adaptive technique for detecting moving shadows and distinguishing them from moving objects in video sequences. Most methods for detecting shadows work in a stat...
Ajay J. Joshi, Nikolaos Papanikolopoulos
98
Voted
MICCAI
2006
Springer
16 years 1 months ago
The Entire Regularization Path for the Support Vector Domain Description
Abstract. The support vector domain description is a one-class classification method that estimates the shape and extent of the distribution of a data set. This separates the data ...
Karl Sjöstrand, Rasmus Larsen
112
Voted
ICONIP
2010
14 years 10 months ago
Multi-view Gender Classification Using Hierarchical Classifiers Structure
In this paper, we propose a hierarchical classifier structure for gender classification based on facial images by reducing the complexity of the original problem. In the proposed f...
Tian-Xiang Wu, Bao-Liang Lu
116
Voted
KDD
2004
ACM
139views Data Mining» more  KDD 2004»
16 years 24 days ago
Learning a complex metabolomic dataset using random forests and support vector machines
Metabolomics is the omics science of biochemistry. The associated data include the quantitative measurements of all small molecule metabolites in a biological sample. These datase...
Young Truong, Xiaodong Lin, Chris Beecher