A Domain Independent Genetic Programming Approach to Automatic Feature Extraction for Image Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Atkins:2011:ADIGPAtAFEfIC,
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title = "A Domain Independent Genetic Programming Approach to
Automatic Feature Extraction for Image Classification",
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author = "Daniel Atkins and Kourosh Neshatian and
Mengjie Zhang",
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pages = "238--245",
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booktitle = "Proceedings of the 2011 IEEE Congress on Evolutionary
Computation",
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year = "2011",
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editor = "Alice E. Smith",
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month = "5-8 " # jun,
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address = "New Orleans, USA",
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organization = "IEEE Computational Intelligence Society",
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publisher = "IEEE Press",
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ISBN = "0-7803-8515-2",
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keywords = "genetic algorithms, genetic programming, automatic
image feature extraction, baseline system, classifier
system, domain independent genetic programming,
human-extracted features, image classification, feature
extraction, image classification",
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DOI = "doi:10.1109/CEC.2011.5949624",
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abstract = "In this paper we explore the application of Genetic
Programming (GP) to the problem of domain-independent
image feature extraction and classification. We propose
a new GP-based image classification system that
extracts image features autonomously, and compare its
performance against a baseline GP-based classifier
system that uses human-extracted features. We found
that the proposed system has a similar performance to
the baseline system, and that GP is capable of evolving
a single program that can both extract useful features
and use those features to classify an image.",
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notes = "CEC2011 sponsored by the IEEE Computational
Intelligence Society, and previously sponsored by the
EPS and the IET.",
- }
Genetic Programming entries for
Daniel L Atkins
Kourosh Neshatian
Mengjie Zhang
Citations