Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry

dc.contributor.author Hemmer, Patrick
dc.contributor.author Kühl, Niklas
dc.contributor.author Schoeffer, Jakob
dc.date.accessioned 2021-12-24T17:27:41Z
dc.date.available 2021-12-24T17:27:41Z
dc.date.issued 2022-01-04
dc.description.abstract Computer-generated imagery of car models has become an indispensable part of car manufacturers' advertisement concepts. They are for instance used in car configurators to offer customers the possibility to configure their car online according to their personal preferences. However, human-led quality assurance faces the challenge to keep up with high-volume visual inspections due to the car models’ increasing complexity. Even though the application of machine learning to many visual inspection tasks has demonstrated great success, its need for large labeled data sets remains a central barrier to using such systems in practice. In this paper, we propose an active machine learning-based quality assurance system that requires significantly fewer labeled instances to identify defective virtual car renderings without compromising performance. By employing our system at a German automotive manufacturer, start-up difficulties can be overcome, the inspection process efficiency can be increased, and thus economic advantages can be realized.
dc.format.extent 10 pages
dc.identifier.doi 10.24251/HICSS.2022.153
dc.identifier.isbn 978-0-9981331-5-7
dc.identifier.uri http://hdl.handle.net/10125/79485
dc.language.iso eng
dc.relation.ispartof Proceedings of the 55th Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Case studies of Artificial Intelligence, Business Intelligence, Analytics Technologies for Industry Platforms
dc.subject active learning
dc.subject computer-generated imagery
dc.subject machine learning
dc.subject quality assurance
dc.title Utilizing Active Machine Learning for Quality Assurance: A Case Study of Virtual Car Renderings in the Automotive Industry
dc.type.dcmi text
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