Genetic Programming with Alternative Search Drivers for Detection of Retinal Blood Vessels
Created by W.Langdon from
gp-bibliography.bib Revision:1.8028
- @InProceedings{Krawiec:2015:evoApplications,
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author = "Krzysztof Krawiec and Mikolaj Pawlak",
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title = "Genetic Programming with Alternative Search Drivers
for Detection of Retinal Blood Vessels",
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booktitle = "18th European Conference on the Applications of
Evolutionary Computation",
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year = "2015",
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editor = "Antonio M. Mora and Giovanni Squillero",
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series = "LNCS",
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volume = "9028",
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publisher = "Springer",
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pages = "554--566",
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address = "Copenhagen",
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month = "8-10 " # apr,
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming, Search
drivers, Binary classification, Image segmentation",
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isbn13 = "978-3-319-16548-6",
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DOI = "doi:10.1007/978-3-319-16549-3_45",
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abstract = "A classification task is a test-based problem, with
examples corresponding to tests. A correct
classification is equivalent to passing a test, while
incorrect to failing it. This applies also to
classifying pixels in an image, viz. image
segmentation. A natural performance indicator in such a
setting is the accuracy of classification, i.e., the
fraction of passed tests. When solving a classification
tasks with genetic programming, it is thus common to
employ this indicator as a fitness function. However,
recent developments in GP as well as some earlier work
suggest that the quality of evolved solutions may
benefit from using other search drivers to guide the
traversal of the space of programs. In this study, we
systematically verify the usefulness of selected
alternative search drivers in the problem of detection
of blood vessels in ophthalmology imaging.",
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notes = "EvoIASP EvoApplications2015 held in conjunction with
EuroGP'2015, EvoCOP2015 and EvoMusArt2015
http://www.evostar.org/2015/cfp_evoapps.php",
- }
Genetic Programming entries for
Krzysztof Krawiec
Mikolaj Pawlak
Citations