CORR
2008
Springer
13 years 4 months ago
2008
Springer
: Applications such as Face Recognition (FR) that deal with high-dimensional data need a mapping technique that introduces representation of low-dimensional features with enhanced ...
IJCAI
2007
13 years 6 months ago
2007
Linear Discriminant Analysis (LDA) is a popular data-analytic tool for studying the class relationship between data points. A major disadvantage of LDA is that it fails to discove...
IPCV
2008
13 years 6 months ago
2008
Linear Discriminant Analysis(LDA) is well-known scheme for feature extraction and dimension reduction. It has been used widely in many applications involving high-dimensional data,...
AAAI
2008
13 years 6 months ago
2008
Recent study has shown that canonical algorithms such as Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) can be obtained from graph based dimensionality ...
ALT
2003
Springer
13 years 8 months ago
2003
Springer
Abstract. A crucial problem in machine learning is to choose an appropriate representation of data, in a way that emphasizes the relations we are interested in. In many cases this ...
CVPR
2009
IEEE
13 years 8 months ago
2009
IEEE
Face detection plays an important role in many vision applications. Since Viola and Jones [1] proposed the first real-time AdaBoost based object detection system, much effort has ...
PCM
2004
Springer
13 years 10 months ago
2004
Springer
In this paper, a novel face recognition method based on Gabor-wavelet and linear discriminant analysis (LDA) is proposed. Given training face images, discriminant vectors are compu...
SIBGRAPI
2005
IEEE
13 years 10 months ago
2005
IEEE
A critical issue of applying Linear Discriminant Analysis (LDA) is both the singularity and instability of the within-class scatter matrix. In practice, particularly in image recog...
ICPR
2006
IEEE
13 years 10 months ago
2006
IEEE
Linear Discriminant Analysis (LDA) is a widely used technique for pattern classification. It seeks the linear projection of the data to a low dimensional subspace where the data ...
ICMCS
2006
IEEE
13 years 10 months ago
2006
IEEE
It is well-known that supervised learning techniques such as linear discriminant analysis (LDA) often suffer from the so called small sample size problem when apply to solve face ...