Analysis of linear and nonlinear dimensionality reduction methods for gender classification of face images

DOI10.1080/00207720500381573zbMath1137.62351OpenAlexW2125325061MaRDI QIDQ5426601

Tim M. Gale, Samarasena Buchala, Ray J. Frank, Neil Davey

Publication date: 13 November 2007

Published in: International Journal of Systems Science (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/2299/597

zbMATH Keywords

principal component analysisintrinsic dimensiondimensionality reductiongender classificationcurvilinear component analysis

Mathematics Subject Classification ID

Multivariate analysis (62H99) Factor analysis and principal components; correspondence analysis (62H25) Image analysis in multivariate analysis (62H35) Pattern recognition, speech recognition (68T10) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (4)

On the combination of kernel principal component analysis and neural networks for process indirect control ⋮ Gender discriminating models from facial surface normals ⋮ The assisted prediction modelling frame with hybridisation and ensemble for business risk forecasting and an implementation ⋮ Multiple proportion case-basing driven CBRE and its application in the evaluation of possible failure of firms

Uses Software

• JAFFE

Cites Work

• Measuring the strangeness of strange attractors
• Independent component analysis, a new concept?
• Intrinsic dimension estimation of data: An approach based on Grassberger-Procaccia's algorithm

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