Producing computationally efficient KPCA-based feature extraction for classification problems

Electronics Letters

Volumn 46, Issue 6, 2010, Pages 452-453

  Xu, Y ^a   Lin, C ^a   Zhao, W ^b  

^a HARBIN INSTITUTE OF TECHNOLOGY   (China)

^b WUHAN UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

BENCHMARK DATASETS; COMPUTATIONALLY EFFICIENT; FEATURE SPACE; KERNEL PRINCIPAL COMPONENT ANALYSIS;

CLASSIFICATION (OF INFORMATION); COMPUTATIONAL EFFICIENCY; PRINCIPAL COMPONENT ANALYSIS;

FEATURE EXTRACTION;

EID: 77949759008     PISSN: 00135194     EISSN: None     Source Type: Journal    
DOI: 10.1049/el.2010.2814     Document Type: Article

References (5)

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2. Yang, J., Jin, Z., Yang, J.-Y., and Zhang, D.: ' Essence of kernel Fisher discriminant: KPCA plus LDA ', Pattern Recognit., 2004, 37, p. 2097-2100 0031-3203
3. Xu, Y., Yang, J.-Y., Lu, J., and Yu, D.-J.: ' An efficient renovation on kernel Fisher discriminant analysis and face recognition experiments ', Pattern Recognit., 2004, 37, p. 2091-2094 0031-3203
4. Xu, Y., Yang, J.-Y., and Yang, J.: ' A reformative kernel Fisher discriminant analysis ', Pattern Recognit., 2004, 37, p. 1299-1302 0031-3203
5. Twining, C., and Taylor, C.: ' Kernel principal component analysis and the construction of non-linear active shape models ', British Machine Vision Conf., Manchester, UK, 2001, 1, p. 23-32