Multi-Objective Genetic Programming for object detection
Created by W.Langdon from
gp-bibliography.bib Revision:1.7954
- @InProceedings{Liddle:2010:cec,
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author = "Thomas Liddle and Mark Johnston and Mengjie Zhang",
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title = "Multi-Objective Genetic Programming for object
detection",
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booktitle = "IEEE Congress on Evolutionary Computation (CEC 2010)",
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year = "2010",
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address = "Barcelona, Spain",
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month = "18-23 " # jul,
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publisher = "IEEE Press",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-1-4244-6910-9",
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abstract = "In object detection, the goals of successfully
discriminating between different kinds of objects
(object classification) and accurately identifying the
positions of all objects of interest in a large image
(object localisation) are potentially in conflict. We
propose a Multi-Objective Genetic Programming (MOGP)
approach to the task of providing a decision-maker with
a diverse set of alternative object detection programs
that balance between high detection rate and low
false-alarm rate. Experiments on two datasets, simple
shapes and photographs of coins, show that it is
difficult for a Single-Objective GP (SOGP) system
(which weights the multiple objectives a priori) to
evolve effective object detectors, but that an MOGP
system is able to evolve a range of effective object
detectors more efficiently.",
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DOI = "doi:10.1109/CEC.2010.5586072",
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notes = "WCCI 2010. Also known as \cite{5586072}",
- }
Genetic Programming entries for
Thomas Liddle
Mark Johnston
Mengjie Zhang
Citations