Visual Learning by Coevolutionary Feature Synthesis
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @Article{Krawiec:2005:SMC,
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author = "Krzysztof Krawiec and Bir Bhanu",
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title = "Visual Learning by Coevolutionary Feature Synthesis",
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journal = "{IEEE} Transactions on System, Man, and Cybernetics --
Part B",
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number = "3",
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pages = "409--425",
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volume = "35",
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month = jun,
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year = "2005",
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keywords = "genetic algorithms, genetic programming, Automatic
programming, feature extraction, pattern recognition,
Computer vision (CV), cooperative coevolution (CC),
evolutionary computation (EC), machine learning (ML),
visual learning",
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URL = "http://ieeexplore.ieee.org/iel5/3477/30862/01430827.pdf",
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DOI = "doi:10.1109/TSMCB.2005.846644",
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size = "17 pages",
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abstract = "A novel genetically inspired visual learning method is
proposed. Given the training raster images, this
general approach induces a sophisticated feature-based
recognition system. It employs the paradigm of
cooperative coevolution to handle the computational
difficulty of this task. To represent the feature
extraction agents, the linear genetic programming is
used. The paper describes the learning algorithm and
provides a firm rationale for its design. Different
architectures of recognition systems are considered
that employ the proposed feature synthesis method. An
extensive experimental evaluation on the demanding
real-world task of object recognition in synthetic
aperture radar (SAR) imagery shows the ability of the
proposed approach to attain high recognition
performance in different operating conditions.",
- }
Genetic Programming entries for
Krzysztof Krawiec
Bir Bhanu
Citations