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Nearest-neighbor classifier motivated marginal discriminant projections for face recognition
Marginal Fisher analysis (MFA) is a representative margin-based learning algorithm for face recognition. A major problem in MFA is how to select appropriate parameters, k1 and k2, to construct theExpand
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Feature extraction using local structure preserving discriminant analysis
Abstract In this paper, an efficient feature extraction method, named local structure preserving discriminant analysis (LSPDA), is presented. LSPDA constructs the local scatter and the between-classExpand
  • 24
Fuzzy local discriminant embedding for image feature extraction
In pattern recognition, feature extraction techniques have been widely employed to reduce the high dimensionality of data. In this paper, we propose a novel algorithm called fuzzy local discriminantExpand
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Discriminant similarity and variance preserving projection for feature extraction
In this paper, a novel supervised dimensionality reduction algorithm called discriminant similarity and variance preserving projection (DSVPP) is presented for feature extraction and recognition.Expand
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Local maximal margin discriminant embedding for face recognition
In this paper, a manifold learning based method named local maximal margin discriminant embedding (LMMDE) is developed for feature extraction. The proposed algorithm LMMDE and other manifold learningExpand
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Fusion of PCA and KFDA for rapid face recognition
  • Cai-Kou Chen, J. Yang, Jian Yang
  • Computer Science
  • ICARCV 8th Control, Automation, Robotics and…
  • 6 December 2004
Kernel method-based feature extraction algorithms such as kernel Fisher discriminant analysis (KFDA) have widely been applied to image recognition tasks such as face recognition. For current featureExpand
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Binary Trademark Image Retrieval Using Region Orientation Information Entropy
This paper presents a new trademark image retrieval method based on the region orientation information entropy. In the first stage, image is rotated according to principal orientation, and the objectExpand
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Two-Dimensional Discriminant Transform Based on Scatter Difference Criterion for Face Recognition
In this paper, a novel image discriminant analysis method, coined two-dimensional discriminant transform based on scatter difference criterion (2DSDD), is developed for image representation. TheExpand
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Hidden space-based nonlinear discriminant feature extraction method
A novel nonlinear feature extraction method based on the scatter difference criterion in hidden space is developed. The main idea is that the original input space is first mapped into a hidden spaceExpand
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Facial Feature Extraction Method Based on Coefficients of Variances
Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) are two popular feature extraction techniques in statistical pattern recognition field. Due to small sample size problem LDAExpand
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