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TASLP
2011
13 years 4 months ago
Time-Frequency Cepstral Features and Heteroscedastic Linear Discriminant Analysis for Language Recognition
Abstract—The shifted delta cepstrum (SDC) is a widely used feature extraction for language recognition (LRE). With a high context width due to incorporation of multiple frames, S...
Weiqiang Zhang, Liang He, Yan Deng, Jia Liu, M. T....
CVPR
2007
IEEE
14 years 12 months ago
Incremental Linear Discriminant Analysis Using Sufficient Spanning Set Approximations
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...
Björn Stenger, Josef Kittler, Roberto Cipolla...
ICIP
2003
IEEE
14 years 11 months ago
Boosting linear discriminant analysis for face recognition
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 ...
ICPR
2006
IEEE
14 years 11 months ago
Bagging Based Efficient Kernel Fisher Discriminant Analysis for Face Recognition
Kernel Fisher Discriminant Analysis (KFDA) has achieved great success in pattern recognition recently. However, the training process of KFDA is too time consuming (even intractabl...
Baochang Zhang, Shiguang Shan, Wen Gao, Xilin Chen...
ICML
2007
IEEE
14 years 10 months ago
Least squares linear discriminant analysis
Linear Discriminant Analysis (LDA) is a well-known method for dimensionality reduction and classification. LDA in the binaryclass case has been shown to be equivalent to linear re...
Jieping Ye