Ensemble-based discriminant learning with boosting for face recognition

In this paper, we propose a novel ensemble-based approach to boost performance of traditional Linear Discriminant Analysis (LDA)-based methods used in face recognition. The ensemble-based approach is based on the recently emerged technique known as "boosting". However, it is generally beli...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems 2006-01, Vol.17 (1), p.166-178
Hauptverfasser:	Lu, J., Plataniotis, K.N., Venetsanopoulos, A.N., Li, S.Z.
Format:	Artikel
Sprache:	eng
Schlagworte:	Accounting Algorithms Applied sciences Artificial Intelligence Authentication Biometrics Boosters Boosting Computer science control theory systems Connectionism. Neural networks Databases, Factual Discriminant analysis Engines Error analysis Exact sciences and technology Expenses Face Face detection Face recognition face recognition (FR) Indexing Learning Linear discriminant analysis Machine learning mixture of linear models Monitoring Neural networks Pattern Recognition, Automated Pattern recognition. Digital image processing. Computational geometry small-sample-size (SSS) problem strong learner Studies
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