Program Size and Pixel Statistics in Genetic Programming for Object Detection
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{zhang2:evows04,
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author = "Mengjie Zhang and Urvesh Bhowan",
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title = "Program Size and Pixel Statistics in Genetic
Programming for Object Detection",
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booktitle = "Applications of Evolutionary Computing,
EvoWorkshops2004: {EvoBIO}, {EvoCOMNET}, {EvoHOT},
{EvoIASP}, {EvoMUSART}, {EvoSTOC}",
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year = "2004",
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month = "5-7 " # apr,
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editor = "Guenther R. Raidl and Stefano Cagnoni and
Jurgen Branke and David W. Corne and Rolf Drechsler and
Yaochu Jin and Colin R. Johnson and Penousal Machado and
Elena Marchiori and Franz Rothlauf and George D. Smith and
Giovanni Squillero",
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series = "LNCS",
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volume = "3005",
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address = "Coimbra, Portugal",
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publisher = "Springer Verlag",
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publisher_address = "Berlin",
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pages = "379--388",
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keywords = "genetic algorithms, genetic programming, evolutionary
computation",
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ISBN = "3-540-21378-3",
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DOI = "doi:10.1007/978-3-540-24653-4_39",
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abstract = "This paper describes an approach to the use of genetic
programming for object detection problems. In this
approach, local region pixel statistics are used to
form three terminal sets. The function set is
constructed by the four standard arithmetic operators
and a conditional operator. A multi-objective fitness
function is constructed based on detection rate, false
alarm rate, false alarm area and program size. This
approach is applied to three object detection problems
of increasing difficulty. The results suggest that the
concentric circular pixel statistics are more effective
than the square features for the coin detection
problems. The fitness function with program size is
more effective and more efficient for these object
detection problems and the evolved genetic programs
using this fitness function are much shorter and easier
to interpret.",
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notes = "EvoWorkshops2004",
- }
Genetic Programming entries for
Mengjie Zhang
Urvesh Bhowan
Citations