We present an algorithm which provides the one-dimensional subspace where the Bayes error is minimized for the C class problem with homoscedastic Gaussian distributions. Our main ...
— The traditional image representations are not suited to conventional classification methods, such as the linear discriminant analysis (LDA), because of the under sample problem...
Dacheng Tao, Xuelong Li, Xindong Wu, Stephen J. Ma...
Writer adaptive handwriting recognition, which has potential of increasing accuracies for a particular user, is the process of converting a writer-independent recognition system t...
This paper presents a new incremental learning solution for Linear Discriminant Analysis (LDA). We apply the concept of the sufficient spanning set approximation in each update st...
In this paper, we propose a new algorithm to boost performance of traditional Linear Discriminant Analysis (LDA)-based face recognition (FR) methods in complex FR tasks, where hig...
Juwei Lu, Konstantinos N. Plataniotis, Anastasios ...