Identity verification based on haptic handwritten Signature: Novel fitness functions for GP framework
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- @InProceedings{Alsulaiman:2013:HAVE,
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author = "Fawaz A. Alsulaiman and Julio J. Valdes and
Abdulmotaleb {El Saddik}",
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booktitle = "IEEE International Symposium on Haptic Audio Visual
Environments and Games (HAVE 2013)",
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title = "Identity verification based on haptic handwritten
Signature: Novel fitness functions for GP framework",
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year = "2013",
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month = oct,
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pages = "98--102",
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keywords = "genetic algorithms, genetic programming, handwriting
recognition, haptic interfaces, GP framework,
evolutionary processes, false rejection rate, haptic
based handwritten signatures, identity verification,
novel fitness functions, Accuracy, Educational
institutions, Evolutionary computation, Gene
expression, Haptic interfaces, Programming",
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DOI = "doi:10.1109/HAVE.2013.6679618",
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size = "5 pages",
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abstract = "Fitness functions are the evaluation measures driving
evolutionary processes towards solutions. In this
paper, three fitness functions are proposed for solving
the unbalanced dataset problem in Haptic-based
handwritten signatures using genetic programming (GP).
The use of these specifically designed fitness
functions produced simpler analytical expressions than
those obtained with currently available fitness
measures, while keeping comparable classification
accuracy. The functions introduced in this paper
capture explicitly the nature of unbalanced data,
exhibit better dimensionality reduction and have better
False Rejection Rate.",
-
notes = "Also known as \cite{6679618}",
- }
Genetic Programming entries for
Fawaz A Alsulaiman
Julio J Valdes
Abdulmotaleb El Saddik
Citations