Predicting Quality of Automated Welding with Machine Learning and Semantics-Reference-Cited by-同舟云学术

Predicting Quality of Automated Welding with Machine Learning and Semantics

Published:2020-10-19 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 29th ACM International Conference on Information & Knowledge Management
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Author:

Zhou Baifan¹,Svetashova Yulia¹,Byeon Seongsu²,Pychynski Tim³,Mikut Ralf⁴,Kharlamov Evgeny⁵

Affiliation:

1. Bosch Corporate Research & Karlsruhe Institute of Technology, Renningen, Germany

2. Bosch Corporate Research & University of Siegen, Renningen, Germany

3. Bosch Corporate Research, Renningen, Germany

4. Karlsruhe Institute of Technology, Karlsruhe, Germany

5. Bosch Center for Artificial Intelligence & University of Oslo, Renningen, Germany

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3340531.3412737

Reference31 articles.

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2. Hana Cevs pivová et almbox. 2004. Roles of medical ontology in association mining Crisp-DM cycle. In ECML/PKDD04. Hana Cevs pivová et almbox. 2004. Roles of medical ontology in association mining Crisp-DM cycle. In ECML/PKDD04.

3. What is smart manufacturing;Chand Sujeet;Time Magazine Wrapper,2010

4. New technology for measuring dynamic resistance and estimating strength in RSW;Cho Yongjoon;MS&T,2000

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