Evolving Texture Image Descriptors Using a Multitree Genetic Programming Representation
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{Al-Sahaf:2017:GECCO,
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author = "Harith Al-Sahaf and Bing Xue and Mengjie Zhang",
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title = "Evolving Texture Image Descriptors Using a Multitree
Genetic Programming Representation",
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booktitle = "Proceedings of the Genetic and Evolutionary
Computation Conference Companion",
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series = "GECCO '17",
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year = "2017",
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isbn13 = "978-1-4503-4939-0",
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address = "Berlin, Germany",
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pages = "219--220",
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size = "2 pages",
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URL = "http://doi.acm.org/10.1145/3067695.3076039",
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DOI = "doi:10.1145/3067695.3076039",
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acmid = "3076039",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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keywords = "genetic algorithms, genetic programming, multiclass
classification, multitree, textures",
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month = "15-19 " # jul,
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abstract = "Image descriptors play very important roles in a wide
range of applications in computer vision and pattern
recognition. In this paper, a multitree genetic
programming method to automatically evolve image
descriptors for multiclass texture image classification
task is proposed. Instead of using domain knowledge,
the proposed method uses only a few instances of each
class to automatically identify a set of features that
are distinctive between the instances of different
classes. The results on seven texture classification
datasets show significant, or comparable, performance
has been achieved by the proposed method compared with
the baseline method and six state-of-the-art methods.",
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notes = "Also known as \cite{Al-Sahaf:2017:ETI:3067695.3076039}
GECCO-2017 A Recombination of the 26th International
Conference on Genetic Algorithms (ICGA-2017) and the
22nd Annual Genetic Programming Conference (GP-2017)",
- }
Genetic Programming entries for
Harith Al-Sahaf
Bing Xue
Mengjie Zhang
Citations