A Gaussian Filter-Based Feature Learning Approach Using Genetic Programming to Image Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InProceedings{bi:2018:AJCAI,
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author = "Ying Bi and Bing Xue and Mengjie Zhang",
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title = "A Gaussian {Filter-Based} Feature Learning Approach
Using Genetic Programming to Image Classification",
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booktitle = "Australasian Joint Conference on Artificial
Intelligence",
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year = "2018",
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editor = "Tanja Mitrovic and Bing Xue and Xiaodong Li",
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volume = "11320",
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series = "LNCS",
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pages = "251--257",
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address = "Wellington, New Zealand",
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month = dec # " 11-14",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, ANN, Feature
learning, Image classification, Gaussian filter,
Evolutionary computation, Feature extraction",
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isbn13 = "978-3-030-03990-5",
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URL = "http://link.springer.com/chapter/10.1007/978-3-030-03991-2_25",
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DOI = "doi:10.1007/978-3-030-03991-2_25",
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abstract = "To learn image features automatically from the
problems being tackled is more effective for
classification. However, it is very difficult due to
image variations and the high dimensionality of image
data. This paper proposes a new feature learning
approach based on Gaussian filters and genetic
programming (GauGP) for image classification. Genetic
programming (GP) is a well-known evolutionary learning
technique and has been applied to many visual tasks,
showing good learning ability and interpretability. In
the proposed GauGP method, a new program structure, a
new function set and a new terminal set are developed,
which allow it to detect small regions from the input
image and to learn discriminative features using
Gaussian filters for image classification. The
performance of GauGP is examined on six different data
sets of varying difficulty and compared with four GP
methods, eight traditional approaches and convolutional
neural networks. The experimental results show GauGP
achieves significantly better or similar performance in
most cases.",
- }
Genetic Programming entries for
Ying Bi
Bing Xue
Mengjie Zhang
Citations