A Fast Incremental Kernel Principal Component Analysis for Online Feature Extraction
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Publisher
Springer Berlin Heidelberg
Link
http://link.springer.com/content/pdf/10.1007/978-3-642-15246-7_45.pdf
Reference11 articles.
1. Abe, S.: Support Vector Machines for Pattern Classification. Springer, London (2005)
2. Ozawa, S., Toh, S.L., Abe, S., Pang, S., Kasabov, N.: Incremental Learning of Feature Space and Classifier for Face Recognition. Neural Networks 18, 575–584 (2005)
3. Hall, P., Marshall, D., Martin, R.: Incremental Eigenanalysis for Classification. In: Proc. of British Machine Vision Conference, pp. 286–295 (1998)
4. Weng, J., Zhang, Y., Hwang, W.S.: Candid Covariance-free Incremental Principal Component Analysis. IEEE Trans. on Pattern Analysis and Machine Intelligence 25, 1034–1040 (2003)
5. Zhao, H., Chi, P., Kwok, J.T.: A Novel Incremental Principal Component Analysis and Its Application for Face Recognition. IEEE Trans. on Systems, Man and Cybern., Part B 36, 873–886 (2006)
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