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» Visual nonlinear discriminant analysis for classifier design
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PAMI
2011
13 years 3 months ago
Kernel Optimization in Discriminant Analysis
— Kernel mapping is one of the most used approaches to intrinsically derive nonlinear classifiers. The idea is to use a kernel function which maps the original nonlinearly separ...
Di You, Onur C. Hamsici, Aleix M. Martínez
ICPR
2008
IEEE
14 years 9 months ago
Understanding visual dictionaries via Maximum Mutual Information curves
Visual dictionaries have been successfully applied to "bags-of-points" image representations for generic object recognition. Usually the choice of low-level interest reg...
Hongli Deng, Wei Zhang
JMM2
2008
157views more  JMM2 2008»
13 years 8 months ago
Multiresolution Feature Based Fractional Power Polynomial Kernel Fisher Discriminant Model for Face Recognition
This paper presents a technique for face recognition which uses wavelet transform to derive desirable facial features. Three level decompositions are used to form the pyramidal mul...
Dattatray V. Jadhav, Jayant V. Kulkarni, Raghunath...
PAA
2002
13 years 8 months ago
Bagging, Boosting and the Random Subspace Method for Linear Classifiers
: Recently bagging, boosting and the random subspace method have become popular combining techniques for improving weak classifiers. These techniques are designed for, and usually ...
Marina Skurichina, Robert P. W. Duin
CVPR
2010
IEEE
14 years 1 months ago
The Automatic Design of Feature Spaces for Local Image Descriptors using an Ensemble of Non-linear Feature Extractors
The design of feature spaces for local image descriptors is an important research subject in computer vision due to its applicability in several problems, such as visual classifi...
Gustavo Carneiro