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» Objective Functions for Feature Discrimination
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ICDAR
2003
IEEE
14 years 4 months ago
Unsupervised Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Word Recognition
In this paper a methodology for feature selection in unsupervised learning is proposed. It makes use of a multiobjective genetic algorithm where the minimization of the number of ...
Marisa E. Morita, Robert Sabourin, Flávio B...
ICANN
2007
Springer
14 years 5 months ago
A Comparison of Features in Parts-Based Object Recognition Hierarchies
Parts-based recognition has been suggested for generalizing from few training views in categorization scenarios. In this paper we present the results of a comparative investigation...
Stephan Hasler, Heiko Wersing, Edgar Körner
CVPR
2011
IEEE
13 years 6 months ago
Mining Discriminative Co-occurrence Patterns for Visual Recognition
The co-occurrence pattern, a combination of binary or local features, is more discriminative than individual features and has shown its advantages in object, scene, and action rec...
Junsong Yuan, Ming Yang, Ying Wu
CVPR
2007
IEEE
15 years 28 days ago
Learning Object Material Categories via Pairwise Discriminant Analysis
In this paper, we investigate linear discriminant analysis (LDA) methods for multiclass classification problems in hyperspectral imaging. We note that LDA does not consider pairwi...
Zhouyu Fu, Antonio Robles-Kelly
ICDAR
2009
IEEE
13 years 8 months ago
Comparative Study of Devnagari Handwritten Character Recognition Using Different Feature and Classifiers
In recent years research towards Indian handwritten character recognition is getting increasing attention. Many approaches have been proposed by the researchers towards handwritte...
Umapada Pal, Tetsushi Wakabayashi, Fumitaka Kimura