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- W1532940624 abstract "In this paper, a new 1-parameter regularized discriminant analysis (1PRDA) algorithm is developed to deal with the small sample size (S3) problem The main limitation in regularization is that the computational complexity of determining the optimal parameters is very high In view of this limitation, we derive a single parameter (t) explicit expression formula for determining the 3 parameters A simple and efficient method is proposed to determine the value of t The proposed 1PRLDA method for face recognition has been evaluated with two public available databases, namely ORL and FERET databases The average recognition accuracy of 50 runs for ORL and FERET database are 96.65% and 94.00% respectively Comparing with existing LDA-based methods in solving the S3 problem, the proposed 1PRLDA method gives the best performance." @default.
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- W1532940624 date "2004-01-01" @default.
- W1532940624 modified "2023-10-16" @default.
- W1532940624 title "A Novel One-Parameter Regularized Linear Discriminant Analysis for Solving Small Sample Size Problem in Face Recognition" @default.
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- W1532940624 doi "https://doi.org/10.1007/978-3-540-30548-4_37" @default.
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