Evolving cascades of voting feature detectors for vehicle detection in satellite imagery
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- @InProceedings{Krawiec:2010:cec2,
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author = "Krzysztof Krawiec and Bartosz Kukawka and
Tomasz Maciejewski",
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title = "Evolving cascades of voting feature detectors for
vehicle detection in satellite imagery",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4244-6910-9",
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URL = "http://www.cs.put.poznan.pl/kkrawiec/pubs/2010CECVehicleDetection.pdf",
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DOI = "doi:10.1109/CEC.2010.5586155",
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size = "8 pages",
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abstract = "We propose an evolutionary method for detection of
vehicles in satellite imagery which involves a large
number of simple elementary features and multiple
detectors trained by genetic programming. The complete
detection system is composed of several detectors that
are chained into a cascade and successively filter out
the negative examples. Each detector is a committee of
genetic programming trees that together vote over the
decision concerning vehicle presence, and is trained
only on the examples classified as positive by the
previous cascade node. The individual trees use typical
arithmetic transformations to aggregate features
selected from a very large collections of Haar-like
features derived from the input image. The paper
presents detailed description of the proposed algorithm
and reports the results of an extensive computational
experiment carried out on real-world satellite images.
The evolved detection system exhibits competitive
sensitivity and relatively low false positive rate for
testing images, despite not making use of
domain-specific knowledge.",
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notes = "WCCI 2010. Also known as \cite{5586155}",
- }
Genetic Programming entries for
Krzysztof Krawiec
Bartosz Kukawka
Tomasz Maciejewski
Citations