A Light in the Dark: Deep Learning Practices for Industrial Computer Vision
Harl M, Herchenbach M, Kruschel S, Hambauer N, Zschech P, Kraus M (2022)
Publication Language: English
Publication Type: Conference contribution, Conference Contribution
Publication year: 2022
Conference Proceedings Title: Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI)
Event location: Nürnberg
URI: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
Open Access Link: https://aisel.aisnet.org/wi2022/student_track/student_track/33/
Abstract
In recent years, large pre-trained deep neural networks (DNNs) have
revolutionized the field of computer vision (CV). Although these DNNs have
been shown to be very well suited for general image recognition tasks, application
in industry is often precluded for three reasons: 1) large pre-trained DNNs are
built on hundreds of millions of parameters, making deployment on many devices
impossible, 2) the underlying dataset for pre training consists of general objects,
while industrial cases often consist of very specific objects, such as structures
on solar wafers, 3) potentially biased pre-trained DNNs raise legal issues for
companies. As a remedy, we study neural networks for CV that we train from
scratch. For this purpose, we use a real-world case from a solar wafer manufacturer.
We find that our neural networks achieve similar performances as pre-trained
DNNs, even though they consist of far fewer parameters and do not rely on
third-party datasets.
Authors with CRIS profile
Maximilian Harl
Lehrstuhl für Digital Industrial Service Systems
Marvin Herchenbach
Lehrstuhl für Digital Industrial Service Systems
Sven Kruschel
Juniorprofessur für Data Analytics
Nico Hambauer
Assistant Professorship for Intelligent Information Systems
Patrick Zschech
Assistant Professorship for Intelligent Information Systems
Mathias Kraus
Juniorprofessur für Data Analytics
Additional Organisation(s)
How to cite
APA:
Harl, M., Herchenbach, M., Kruschel, S., Hambauer, N., Zschech, P., & Kraus, M. (2022). A Light in the Dark: Deep Learning Practices for Industrial Computer Vision. In Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI). Nürnberg, DE.
MLA:
Harl, Maximilian, et al. "A Light in the Dark: Deep Learning Practices for Industrial Computer Vision." Proceedings of the Proceedings of the 17th International Conference on Wirtschaftsinformatik (WI), Nürnberg 2022.
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