Automatically Extracting Features Using Genetic Programming for Low-Quality Fish Image Classification
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Yan:2021:CEC,
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author = "Zichu Yan and Ying Bi and Bing Xue and Mengjie Zhang",
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booktitle = "2021 IEEE Congress on Evolutionary Computation (CEC)",
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title = "Automatically Extracting Features Using Genetic
Programming for Low-Quality Fish Image Classification",
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year = "2021",
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editor = "Yew-Soon Ong",
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pages = "2015--2022",
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address = "Krakow, Poland",
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month = "28 " # jun # "-1 " # jul,
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isbn13 = "978-1-7281-8393-0",
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abstract = "Fish image classification is an important task in the
protection of precious marine resources. However, this
task is difficult due to the low-quality images and the
high inter-class variations across images. Most
existing methods use high-quality images for
classification and need domain knowledge. In this
paper, we develop a genetic programming (GP) approach
to automatically selecting image operators to deal with
the low-quality images and extracting effective
features from these images for low-quality fish image
classification. To achieve this, a new program
structure and a new function set are developed. With
these designs, the proposed GP approach can evolve
solutions that use effective filtering or restoration
operators to deal with the input image, select
informative regions from the fish image, and extract
effective global and/or local features from the fish
images. The results show that the proposed approach
achieves significantly better performance than 12
benchmark methods, including a state-of-the-art GP
approach, on the well-known fish image classification
dataset. Further analysis shows the high
interpretability of the evolved GP trees and the
effectiveness of the employed image filtering or
restoration operators.",
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keywords = "genetic algorithms, genetic programming, Filtering,
Evolutionary computation, Benchmark testing, Feature
extraction, Fish, Image filtering",
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DOI = "doi:10.1109/CEC45853.2021.9504737",
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notes = "Also known as \cite{9504737}",
- }
Genetic Programming entries for
Zichu Yan
Ying Bi
Bing Xue
Mengjie Zhang
Citations