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BMCBI
2005
89views more  BMCBI 2005»
13 years 9 months ago
An empirical analysis of training protocols for probabilistic gene finders
Background: Generalized hidden Markov models (GHMMs) appear to be approaching acceptance as a de facto standard for state-of-the-art ab initio gene finding, as evidenced by the re...
William H. Majoros, Steven Salzberg
IJON
2010
178views more  IJON 2010»
13 years 8 months ago
An empirical study of two typical locality preserving linear discriminant analysis methods
: Laplacian Linear Discriminant Analysis (LapLDA) and Semi-supervised Discriminant Analysis (SDA) are two recently proposed LDA methods. They are developed independently with the a...
Lishan Qiao, Limei Zhang, Songcan Chen
CVPR
2005
IEEE
14 years 12 months ago
Fisher+Kernel Criterion for Discriminant Analysis
We simultaneously approach two tasks of nonlinear discriminant analysis and kernel selection problem by proposing a unified criterion, Fisher+Kernel Criterion. In addition, an eff...
Shu Yang, Shuicheng Yan, Dong Xu, Xiaoou Tang, Cha...
ICCV
2007
IEEE
14 years 11 months ago
Semi-supervised Discriminant Analysis
Linear Discriminant Analysis (LDA) has been a popular method for extracting features which preserve class separability. The projection vectors are commonly obtained by maximizing ...
Deng Cai, Xiaofei He, Jiawei Han
FGR
2008
IEEE
155views Biometrics» more  FGR 2008»
14 years 4 months ago
Biased discriminant analysis using composite vectors for eye detection
We propose a new discriminant analysis using composite vectors for eye detection. A composite vector consists of a number of pixels inside a window on an image. The covariance of ...
Chunghoon Kim, Matthew Turk, Chong-Ho Choi