Improved Assessment of Offshore Helideck Marking Standards’ Compliance using Optimized Machine Learning Principles in the U.S. Gulf of Mexico

Mitchell Bosman, Kazim Sekeroglu, Ghassan Alkadi

2022

Abstract

There is an unknown number of offshore helidecks in the U.S. Gulf of Mexico that comply with a specific marking standard. This is a direct result from the lack of national regulations enforced. The purpose of this research is to improve the assessment of offshore helideck marking standards’ compliance using optimized machine learning principles. Using two different phases and employing the transfer learning approach, an optimized machine learning algorithm is generated to classify offshore helidecks from photographs into CAP 437, HSAC RP 161 or None. Results show that this model can identify marking standards being used with an accuracy of 95.7 percent. Therefore, demonstrating that the machine learning principles used can improve the assessment of offshore helideck marking standards’ compliance.

Paper Citation

in Harvard Style

Bosman M., Sekeroglu K. and Alkadi G. (2022). Improved Assessment of Offshore Helideck Marking Standards’ Compliance using Optimized Machine Learning Principles in the U.S. Gulf of Mexico. In Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE, ISBN 978-989-758-563-0, pages 234-241. DOI: 10.5220/0011108800003209

in Bibtex Style

@conference{improve22,
author={Mitchell Bosman and Kazim Sekeroglu and Ghassan Alkadi},
title={Improved Assessment of Offshore Helideck Marking Standards’ Compliance using Optimized Machine Learning Principles in the U.S. Gulf of Mexico},
booktitle={Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,},
year={2022},
pages={234-241},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011108800003209},
isbn={978-989-758-563-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on Image Processing and Vision Engineering - Volume 1: IMPROVE,
TI - Improved Assessment of Offshore Helideck Marking Standards’ Compliance using Optimized Machine Learning Principles in the U.S. Gulf of Mexico
SN - 978-989-758-563-0
AU - Bosman M.
AU - Sekeroglu K.
AU - Alkadi G.
PY - 2022
SP - 234
EP - 241
DO - 10.5220/0011108800003209