Performance of various training algorithms on scene illumination classification

Citation

Hesamian, Mohammad Hesam and Mashohor, Syamsiah and Saripan, M. Iqbal and Wan Adnan, Wan Azizun and Hesamian, B. and Hooshyari, M. M. (2015) Performance of various training algorithms on scene illumination classification. In: 2015 IEEE Student Conference on Research and Development (SCOReD), 13-14 Dec. 2015, Berjaya Times Square Hotel, Kuala Lumpur, Malaysia. (pp. 66-71).

Abstract

The increasing number of training algorithms along with their convincing results will make this question that which algorithm will be more efficient. This study aims to perform some widespread tests on some well-known training algorithms (Levenberg-Marquardt, Resilient back propagation and Scaled conjugate gradient) to evaluate their performance for scene illumination classification. The results presented by this research can provide a reliable guide line for choosing the most appropriate training algorithm depends on the problem specification. The results of this study select the LM training method with the accuracy of 94.41% as the most accurate and RP as the most quick method with response time of 0.426 s.

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Additional Metadata

Item Type:	Conference or Workshop Item (Paper)
Divisions:	Faculty of Engineering
DOI Number:	https://doi.org/10.1109/SCORED.2015.7449421
Publisher:	IEEE
Keywords:	Neural network; Scene illumination classification; Training algorithms
Depositing User:	Nabilah Mustapa
Date Deposited:	14 Jul 2016 08:52
Last Modified:	14 Jul 2016 08:52
Altmetrics:	http://www.altmetric.com/details.php?domain=psasir.upm.edu.my&doi=10.1109/SCORED.2015.7449421
URI:	http://psasir.upm.edu.my/id/eprint/47714
Statistic Details:	View Download Statistic

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