Object categorization using Cartesian Genetic Programming (CGP) and CGP-Evolved Artificial Neural Network
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @InProceedings{Salahuddin:2010:ICCAIE,
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author = "Sumayyea Salahuddin and Maryam Mahsal Khan",
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title = "Object categorization using Cartesian Genetic
Programming (CGP) and CGP-Evolved Artificial Neural
Network",
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booktitle = "2010 International Conference on Computer Applications
and Industrial Electronics (ICCAIE)",
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year = "2010",
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month = "5-8 " # dec,
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pages = "191--196",
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abstract = "In this paper, we address the problem of recognising
object categories by proposing a learning model based
on evolutionary algorithm that takes unsegmented,
complex images which is tolerant to 2D affine
transformations such as scaling and translation in the
image plane and 3D transformations of an object such as
illumination changes and rotation in depth. To achieve
this, first object features are extracted from an image
using modified Bag of Keypoints model and then learning
and classification is performed through evolutionary
network classifiers i.e. Cartesian Genetic Programming
(CGP) and Cartesian Genetic Programming Evolved
Artificial Neural Network (CG-PANN). Our empirical
evaluations show that proposed network classifiers
exhibit outstanding ability of learning from fewer
training examples with good accuracy. Results are
compared with NEAT-Evolved Artificial Neural Network
classifier which shows clearly that our network
classifiers outperform and generalise better than
NEAT.",
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keywords = "genetic algorithms, genetic programming, Cartesian
genetic programming, CGP-evolved artificial neural
network, NEAT-evolved artificial neural network
classifier, affine transformations, evolutionary
algorithm, evolutionary network classifiers, image
plane, learning model, modified bag of keypoints model,
object categorisation, object feature extraction,
feature extraction, image classification, neural nets,
object recognition, transforms",
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DOI = "doi:10.1109/ICCAIE.2010.5735073",
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notes = "Dept. of Comput. Syst. Eng., Univ. of Eng. & Technol.,
Peshawar, Pakistan Also known as \cite{5735073}",
- }
Genetic Programming entries for
Sumayyea Salahuddin
Maryam Mahsal Khan
Citations