Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
Feature Selection: Evaluation, Application, and Small Sample Performance
IEEE Transactions on Pattern Analysis and Machine Intelligence
Classification Using Adaptive Wavelets for Feature Extraction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Extraction From Wavelet Coefficients for Pattern Recognition Tasks
IEEE Transactions on Pattern Analysis and Machine Intelligence
Mode-Finding for Mixtures of Gaussian Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Multiclass Linear Dimension Reduction by Weighted Pairwise Fisher Criteria
IEEE Transactions on Pattern Analysis and Machine Intelligence
Feature Extraction Based on Decision Boundaries
IEEE Transactions on Pattern Analysis and Machine Intelligence
Linear Dimensionality Reduction via a Heteroscedastic Extension of LDA: The Chernoff Criterion
IEEE Transactions on Pattern Analysis and Machine Intelligence
A novel approach to feature selection based on analysis of class regions
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
An efficient fuzzy classifier with feature selection based on fuzzyentropy
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Image Processing
Two efficient connectionist schemes for structure preserving dimensionality reduction
IEEE Transactions on Neural Networks
The feature extraction procedure for pattern recognition with learning using genetic algorithm
SMO'07 Proceedings of the 7th WSEAS International Conference on Simulation, Modelling and Optimization
ICAISC '08 Proceedings of the 9th international conference on Artificial Intelligence and Soft Computing
A Discriminant Analysis Method for Face Recognition in Heteroscedastic Distributions
ICB '09 Proceedings of the Third International Conference on Advances in Biometrics
Online preprocessing of handwritten Gurmukhi strokes
Machine Graphics & Vision International Journal
Intelligent visual recognition and classification of cork tiles with neural networks
IEEE Transactions on Neural Networks
The bayes-optimal feature extraction procedure for pattern recognition using genetic algorithm
ICANN'06 Proceedings of the 16th international conference on Artificial Neural Networks - Volume Part I
A complete and fully automated face verification system on mobile devices
Pattern Recognition
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A parametric linear feature extraction method is proposed for multiclass classification. The skeleton of the proposed method consists of two types of schemes that are complementary to each other with regard to the discriminant information used. The approximate pairwise accuracy criterion (aPAC) and the common-mean feature extraction (CMFE) are chosen to exploit the discriminant information about class mean and about class covariance, respectively. Choosing aPAC rather than the linear discriminant analysis (LDA) can also resolve the problem of overemphasized large distances introduced by LDA, while maintaining other decent properties of LDA. To alleviate the suboptimum problem caused by a direct cascading of the two different types of schemes, there should be a mechanism for sorting and merging features based on their effectiveness. Usage of a sample-based classification error estimation for evaluation of effectiveness of features usually costs a lot of computational time. Therefore, we develop a fast spanning-tree-based parametric classification accuracy estimator as an intermediary for the aPAC and CMFE combination. The entire framework is parametric-based. This avoids paying a costly price in computation, which normally happens to the sample-based approach. Our experiments have shown that the proposed method can achieve a satisfactory performance on real data as well as simulated data.