Land Cover/Land Use Multiclass Classification Using GP with Geometric Semantic Operators
Created by W.Langdon from
gp-bibliography.bib Revision:1.7970
- @InProceedings{Castelli:evoapps13,
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author = "Mauro Castelli and Sara Silva and
Leonardo Vanneschi and Ana Cabral and Maria J. Vasconcelos and
Luis Catarino and Joao M. B. Carreiras",
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title = "Land Cover/Land Use Multiclass Classification Using GP
with Geometric Semantic Operators",
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booktitle = "Applications of Evolutionary Computing,
EvoApplications 2013: EvoCOMNET, EvoCOMPLEX, EvoENERGY,
EvoFIN, EvoGAMES, EvoIASP, EvoINDUSTRY, EvoNUM, EvoPAR,
EvoRISK, EvoROBOT, EvoSTOC",
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year = "2013",
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month = "3-5 " # apr,
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editor = "Anna I. Esparcia-Alcazar and Antonio Della Cioppa and
Ivanoe {De Falco} and Ernesto Tarantino and
Carlos Cotta and Robert Schaefer and Konrad Diwold and
Kyrre Glette and Andrea Tettamanzi and
Alexandros Agapitos and Paolo Burrelli and J. J. Merelo and
Stefano Cagnoni and Mengjie Zhang and Neil Urquhart and Kevin Sim and
Aniko Ekart and Francisco {Fernandez de Vega} and
Sara Silva and Evert Haasdijk and Gusz Eiben and
Anabela Simoes and Philipp Rohlfshagen",
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series = "LNCS",
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volume = "7835",
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publisher = "Springer Verlag",
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address = "Vienna",
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publisher_address = "Berlin",
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pages = "334--343",
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organisation = "EvoStar",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-37191-2",
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DOI = "doi:10.1007/978-3-642-37192-9_34",
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size = "10 pages",
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abstract = "Multiclass classification is a common requirement of
many land cover/land use applications, one of the
pillars of land science studies. Even though genetic
programming has been applied with success to a large
number of applications, it is not particularly suited
for multi-class classification, thus limiting its use
on such studies. In this paper we take a step forward
towards filling this gap, investigating the performance
of recently defined geometric semantic operators on two
land cover/land use multiclass classification problems
and also on a benchmark problem. Our results clearly
indicate that genetic programming using the new
geometric semantic operators outperforms standard
genetic programming for all the studied problems, both
on training and test data.",
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notes = "
EvoApplications2013 held in conjunction with
EuroGP2013, EvoCOP2013, EvoBio'2013 and EvoMusArt2013",
- }
Genetic Programming entries for
Mauro Castelli
Sara Silva
Leonardo Vanneschi
Ana Isabel Rosa Cabral
Maria Jose Vasconcelos
Luis Catarino
Joao Manuel de Brito Carreiras
Citations