Extracting Image Features for Classification By Two-Tier Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Al-Sahaf:2012:CEC,
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title = "Extracting Image Features for Classification By
Two-Tier Genetic Programming",
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author = "Harith Al-Sahaf and Andy Song and
Kourosh Neshatian and Mengjie Zhang",
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pages = "1630--1637",
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booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary
Computation",
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year = "2012",
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editor = "Xiaodong Li",
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month = "10-15 " # jun,
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DOI = "doi:10.1109/CEC.2012.6256412",
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address = "Brisbane, Australia",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, Evolutionary
Computer Vision",
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abstract = "Image classification is a complex but important task
especially in the areas of machine vision and image
analysis such as remote sensing and face recognition.
One of the challenges in image classification is
finding an optimal set of features for a particular
task because the choice of features has direct impact
on the classification performance. However the goodness
of a feature is highly problem dependent and often
domain knowledge is required. To address these issues
we introduce a Genetic Programming (GP) based image
classification method, Two-Tier GP, which directly
operates on raw pixels rather than features. The first
tier in a classifier is for automatically defining
features based on raw image input, while the second
tier makes decision. Compared to conventional feature
based image classification methods, Two-Tier GP
achieved better accuracies on a range of different
tasks. Furthermore by using the features defined by the
first tier of these Two-Tier GP classifiers,
conventional classification methods obtained higher
accuracies than classifying on manually designed
features. Analysis on evolved Two-Tier image
classifiers shows that there are genuine features
captured in the programs and the mechanism of achieving
high accuracy can be revealed. The Two-Tier GP method
has clear advantages in image classification, such as
high accuracy, good interpretability and the removal of
explicit feature extraction process.",
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notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the
EPS and the IET.",
- }
Genetic Programming entries for
Harith Al-Sahaf
Andy Song
Kourosh Neshatian
Mengjie Zhang
Citations