Improving Classification on Images by Extracting and Transferring Knowledge in Genetic Programming
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Iqbal:2016:CEC,
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author = "Muhammad Iqbal and Mengjie Zhang and Bing Xue",
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title = "Improving Classification on Images by Extracting and
Transferring Knowledge in Genetic Programming",
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booktitle = "Proceedings of 2016 IEEE Congress on Evolutionary
Computation (CEC 2016)",
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year = "2016",
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editor = "Yew-Soon Ong",
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pages = "3582--3589",
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address = "Vancouver",
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month = "24-29 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-5090-0623-6",
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DOI = "doi:10.1109/CEC.2016.7744243",
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abstract = "Genetic programming (GP) is a well established
evolutionary computation technique that automatically
generates a computer program to solve a given problem.
GP has been successfully used to solve optimization,
symbolic regression and classification problems.
Transfer learning in GP has been investigated to learn
various Boolean and symbolic regression problems.
However, there has been not much work on transfer
learning in GP for image classification problems. In
this paper, we propose a new technique to use transfer
learning in GP to learn image classification problems.
The developed method has been compared with the
baseline GP method on three image classification
benchmarks. The obtained results indicate that transfer
learning has significantly improved the classification
accuracy in learning various rotated and noisy versions
of the tested image classification problems.",
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notes = "WCCI2016",
- }
Genetic Programming entries for
Muhammad Iqbal
Mengjie Zhang
Bing Xue
Citations