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Region Based Image Preprocessor for Feed-Forward Perceptron Based Systems

Greenhow, Keith and Johnson, Colin G. (2014) Region Based Image Preprocessor for Feed-Forward Perceptron Based Systems. In: Zeng, Zhigang and Li, Yangmin and King, Irwin, eds. Advances in Neural Networks – ISNN 2014 11th International Symposium on Neural Networks. Lecture Notes in Computer Science . Springer, Cham, Switzerland, pp. 414-422. ISBN 978-3-319-12435-3. E-ISBN 978-3-319-12436-0. (doi:10.1007/978-3-319-12436-0_46) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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Abstract

In this paper, we investigate the notion that there may be alternate methods, beyond typical rectilinear interpolations such as Bilinear Interpolation, that have a greater suitability for use in visual/image preprocessors for Artificial Neural Networks. We present a novel method for down-sampling image data in preparation for a Feed-Forward Perceptron system assisted by a neural usefulness metric, inspired by those common to pruning algorithms. This new method achieves greater accuracy compared to the same system using by Bilinear Interpolation, and has a reduced computational time.

Item Type: Book section
DOI/Identification number: 10.1007/978-3-319-12436-0_46
Uncontrolled keywords: artificial neural networks; preprocessor; image processing; salience; relevance assessment
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.87 Neural computers, neural networks
Divisions: Faculties > Sciences > School of Computing > Computational Intelligence Group
Depositing User: Colin Johnson
Date Deposited: 04 Nov 2015 10:42 UTC
Last Modified: 14 Oct 2019 10:57 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/51436 (The current URI for this page, for reference purposes)
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
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