Face recognition based on the uncorrelated discriminant transformation

By Zhong Jin, Jing-yu Yang, Zhongyuan Hu, Z. Lou. Pattern Recognition, 2001

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Least squares linear discriminant analysis (2007, methodology): “The Uncorrelated LDA algorithm (ULDA) [31] is an extension of the original ULDA algorithm [ 21 ] to high-dimensional and undersampled data.”
A new method of feature fusion and its application in image recognition (2005, methodology): “A method of the uncorrelated optimal discriminant vectors is proposed by Zhong Jin et al. [26,27], and has been applied to the realms of face recognition and character recognition, which get a good performance.”
Classification of Hyperspectral Images With Regularized Linear Discriminant Analysis (2009, methodology): “More details on the OLDA and ULDA methods can be found in [1], [25], [26], [32], and [33].”
Face recognition with radial basis function (RBF) neural networks (2002, methodology): “and eight patterns per person in [29]); some results were evaluated based on the best performance of one run, such as [41], [42]; some experiments were performed based on part of the database [40].”
Feature dimensionality reduction: a review (2022, methodology): “Statistically uncorrelated identification analysis method [54] and other methods”