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Regioned Downsample for ANN Image Classification: Alternate Selection Methods

Greenhow, Keith, Johnson, Colin G. (2015) Regioned Downsample for ANN Image Classification: Alternate Selection Methods. In: 2015 SAI Intelligent Systems Conference (IntelliSys). . pp. 793-797. IEEE, Red Hood, NY, USA ISBN 978-1-4673-7607-5. (doi:10.1109/IntelliSys.2015.7361231)

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http://dx.doi.org/10.1109/IntelliSys.2015.7361231

Abstract

In an earlier paper, a novel method to pre-process image data for use in Artificial Neural-Network (ANN) classification was presented. This method requires an additional training stage prior to the main learning phase of the ANN. In this extra stage, an additional algorithm (a Selection method) is used to generate the data that is required to construct the final pre-processor. As part of the introduction of that method, it was presented with a single Selection method that was termed Saliency Heat Mapping. This paper will present a number of alternative Selection methods and compare how effective they are against a sample problem.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/IntelliSys.2015.7361231
Subjects: Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming,
Q Science > QA Mathematics (inc Computing science) > QA 76 Software, computer programming, > QA76.87 Neural computers, neural networks
Divisions: Faculties > Sciences > School of Computing
Depositing User: Colin Johnson
Date Deposited: 13 Dec 2018 10:01 UTC
Last Modified: 30 May 2019 08:33 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/70994 (The current URI for this page, for reference purposes)
Johnson, Colin G.: https://orcid.org/0000-0002-9236-6581
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