Similarity Measures for Visual Comparison and Retrieval of Test Data in Aluminum Production

Nikolina Jekic, Belgin Mutlu, Belgin Mutlu, Manuela Schreyer, Steffen Neubert, Tobias Schreck

Abstract

Monitoring, analyzing and determining the production quality in a complex and long-running process such as in the aluminum production is a challenging task. The domain experts are often overwhelmed by the flood of data being generated and collected and have difficulties to analyze and interpret the results. Likewise, experts find it difficult to identify patterns in their data that may indicate deviations and anomalies that lead to unstable processes and lower product quality. We aim to support domain experts in the production data exploration and identifying meaningful patterns. The existing research covers a broad spectrum of pattern recognition methodologies that can be potentially applied to elicit patterns in data collected from industrial production. Hence, in this paper, we further analyze the applicability of different similarity measures to effectively recognize specific ultrasonic patterns which may indicate critical process deviations in aluminum production.

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Paper Citation


in Harvard Style

Jekic N., Mutlu B., Schreyer M., Neubert S. and Schreck T. (2021). Similarity Measures for Visual Comparison and Retrieval of Test Data in Aluminum Production.In Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP, ISBN 978-989-758-488-6, pages 210-218. DOI: 10.5220/0010309302100218


in Bibtex Style

@conference{ivapp21,
author={Nikolina Jekic and Belgin Mutlu and Manuela Schreyer and Steffen Neubert and Tobias Schreck},
title={Similarity Measures for Visual Comparison and Retrieval of Test Data in Aluminum Production},
booktitle={Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP,},
year={2021},
pages={210-218},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010309302100218},
isbn={978-989-758-488-6},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 16th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 1: IVAPP,
TI - Similarity Measures for Visual Comparison and Retrieval of Test Data in Aluminum Production
SN - 978-989-758-488-6
AU - Jekic N.
AU - Mutlu B.
AU - Schreyer M.
AU - Neubert S.
AU - Schreck T.
PY - 2021
SP - 210
EP - 218
DO - 10.5220/0010309302100218