154 search results - page 12 / 31 » Feature Extraction for Outlier Detection in High-Dimensional... |
142
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CIRA
2007
IEEE
15 years 8 months ago
2007
IEEE
Abstract—In classical image classification approaches, lowlevel features have been used. But the high dimensionality of feature spaces poses a challenge in terms of feature selec...
117
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NIPS
2008
15 years 3 months ago
2008
Kernel Principal Component Analysis (KPCA) is a popular generalization of linear PCA that allows non-linear feature extraction. In KPCA, data in the input space is mapped to highe...
108
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ICASSP
2011
IEEE
14 years 5 months ago
2011
IEEE
Spike detection and sorting is a fundamental step in the analysis of extracellular neural recording. Here, we propose a combined spike detection-feature extraction algorithm that ...
110
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IJDMB
2008
15 years 1 months ago
2008
: Computational classification of proteins using methods such as string kernels and Fisher-SVM has demonstrated great success. However, the resulting models do not offer an immedia...
129
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CVPR
2012
IEEE
13 years 4 months ago
2012
IEEE
The problem of simultaneous feature extraction and selection, for classifier design, is considered. A new framework is proposed, based on boosting algorithms that can either 1) s...