Genetic Engineering of Hierarchical Fuzzy Regional Representations for Handwritten Character Recognition
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- @Article{Gagne:2006:ijDAR,
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author = "Christian Gagne and Marc Parizeau",
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title = "Genetic Engineering of Hierarchical Fuzzy Regional
Representations for Handwritten Character Recognition",
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journal = "International Journal on Document Analysis and
Recognition",
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year = "2006",
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volume = "8",
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number = "4",
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pages = "223--231",
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month = sep,
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keywords = "genetic algorithms, genetic programming",
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URL = "http://vision.gel.ulaval.ca/fr/publications/Id_607/PublDetails.php",
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DOI = "doi:10.1007/s10032-005-0005-6",
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abstract = "This paper presents a genetic programming based
approach for optimising the feature extraction step of
a handwritten character recogniser. This recognizer
uses a simple multilayer perceptron as a classifier and
operates on a hierarchical feature space of
orientation, curvature, and centre of mass primitives.
The nodes of the hierarchy represent rectangular
sub-regions of their parent node, the tree root
corresponding to the character's bounding box. Within
each sub-region, a variable number of fuzzy features
are extracted. Genetic programming is used to
simultaneously learn the best hierarchy and the best
combination of fuzzy features. Moreover, the fuzzy
features are not predetermined, they are inferred from
the evolution process which runs a two-objective
selection operator. The first objective maximises the
recognition rate, and the second minimises the feature
space size. Results on Unipen data show that, using
this approach, robust representations could be obtained
that out-performed comparable human-designed
hierarchical fuzzy regional representations.",
- }
Genetic Programming entries for
Christian Gagne
Marc Parizeau
Citations