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A generalised K-L expansion method which can deal with small sample size and high-dimensional problems

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Publication:1400851
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DOI10.1007/S10044-002-0177-3zbMath1035.68109OpenAlexW2008101758WikidataQ57811940 ScholiaQ57811940MaRDI QIDQ1400851

D. Massart

Publication date: 14 August 2003

Published in: PAA. Pattern Analysis and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10044-002-0177-3


zbMATH Keywords

Feature extractionPrincipal Component AnalysisFace recognitionHigh dimensional problemK-L expansionSmall sample size problem


Mathematics Subject Classification ID

Pattern recognition, speech recognition (68T10)


Related Items (5)

A new perspective to null linear discriminant analysis method and its fast implementation using random matrix multiplication with scatter matrices ⋮ A Supervised Feature Extraction Algorithm for Multi-class ⋮ A multi-objective memetic algorithm for low rank and sparse matrix decomposition ⋮ A discriminant model for the pattern recognition of linearly independent samples ⋮ Post-processed LDA for face and palmprint recognition: what is the rationale


Uses Software

  • ORL face






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