Figure of Merit Based Fitness Functions in Genetic Programming for Edge Detection
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Fu:2012:SEAL,
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author = "Wenlong Fu and Mark Johnston and Mengjie Zhang",
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title = "Figure of Merit Based Fitness Functions in Genetic
Programming for Edge Detection",
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booktitle = "The Ninth International Conference on Simulated
Evolution And Learning, SEAL 2012",
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year = "2012",
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editor = "Lam Thu Bui and Yew-Soon Ong and Nguyen Xuan Hoai and
Hisao Ishibuchi and Ponnuthurai Nagaratnam Suganthan",
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volume = "7673",
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series = "Lecture Notes in Computer Science",
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pages = "22--31",
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address = "Vietnam",
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month = dec # " 16-19",
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organisation = "Faculty of Information Technology, Le Quy Don
Technical University",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Edge
Detection, Figure of Merit",
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isbn13 = "978-3-642-34858-7",
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DOI = "doi:10.1007/978-3-642-34859-4_3",
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size = "10 pages",
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abstract = "The figure of merit (FOM) is popular for testing an
edge detector's performance, but there are very few
reports using FOM as an evaluation method in Genetic
Programming (GP). In this study, FOM is investigated as
a fitness function in GP for edge detection. Since FOM
has some drawbacks from type II errors, new fitness
functions are developed based on FOM in order to
address these weaknesses. Experimental results show
that FOM can be used to evolve GP edge detectors that
perform better than the Sobel detector, and the new
fitness functions clearly improve the ability of GP
edge detectors to find edge points and give a single
response on edges, compared with the fitness function
using FOM.",
- }
Genetic Programming entries for
Wenlong Fu
Mark Johnston
Mengjie Zhang
Citations