| Machine learning with domain knowledge for predictive quality monitoring in resistance spot welding B Zhou, T Pychynski, M Reischl, E Kharlamov, R Mikut Journal of Intelligent Manufacturing 33 (4), 1139-1163, 2022 | 60 | 2022 |
| Ontology-enhanced machine learning: a Bosch use case of welding quality monitoring Y Svetashova*, B Zhou*, T Pychynski, S Schmidt, Y Sure-Vetter, R Mikut, ... International Semantic Web Conference, 531-550, 2020 | 45 | 2020 |
| Predicting quality of automated welding with machine learning and semantics: a Bosch case study B Zhou, Y Svetashova, S Byeon, T Pychynski, R Mikut, E Kharlamov Proceedings of the 29th ACM International Conference on Information …, 2020 | 36 | 2020 |
| SemML: Facilitating development of ML models for condition monitoring with semantics B Zhou*, Y Svetashova*, A Gusmao, A Soylu, G Cheng, R Mikut, A Waaler, ... Journal of Web Semantics 71, 100664, 2021 | 32 | 2021 |
| High accuracy beam splitting using spatial light modulator combined with machine learning algorithms D Mikhaylov, B Zhou, T Kiedrowski, R Mikut, AF Lasagni Optics and Lasers in Engineering 121, 227-235, 2019 | 28 | 2019 |
| SemFE: Facilitating ML pipeline development with semantics B Zhou, Y Svetashova, T Pychynski, I Baimuratov, A Soylu, E Kharlamov Proceedings of the 29th ACM International Conference on Information …, 2020 | 25 | 2020 |
| Scaling usability of ML analytics with knowledge graphs: exemplified with a Bosch welding case B Zhou, D Zhou, J Chen, Y Svetashova, G Cheng, E Kharlamov Proceedings of the 10th International Joint Conference on Knowledge Graphs …, 2021 | 22 | 2021 |
| Comparison of machine learning approaches for time-series-based quality monitoring of resistance spot welding (RSW) B Zhou, T Pychynski, M Reischl, R Mikut Archives of Data Science, Series A (Online First) 5 (1), 13, 2018 | 22 | 2018 |
| Improving root cause analysis by detecting and removing transient changes in oscillatory time series with application to a 1, 3-butadiene process B Zhou, M Chioua, M Bauer, JC Schlake, NF Thornhill Industrial & Engineering Chemistry Research 58 (26), 11234-11250, 2019 | 20 | 2019 |
| Enhancing knowledge graph generation with ontology reshaping–Bosch case D Zhou, B Zhou, Z Zheng, EV Kostylev, G Cheng, E Jimenez-Ruiz, ... European Semantic Web Conference, 299-302, 2022 | 19 | 2022 |
| The data value quest: a holistic semantic approach at Bosch B Zhou, Z Zheng, D Zhou, G Cheng, E Jiménez-Ruiz, TK Tran, ... European Semantic Web Conference, 287-290, 2022 | 18 | 2022 |
| Executable Knowledge Graphs for Machine Learning: A Bosch Case of Welding Monitoring Z Zheng*, B Zhou*, D Zhou, X Zheng, G Cheng, A Soylu, E Kharlamov International Semantic Web Conference, 791-809, 2022 | 18 | 2022 |
| Towards generalized welding ontology in line with ISO and knowledge graph construction M Yahya, B Zhou, Z Zheng, D Zhou, JG Breslin, MI Ali, E Kharlamov European Semantic Web Conference, 83-88, 2022 | 17 | 2022 |
| Query-based industrial analytics over knowledge graphs with ontology reshaping Z Zheng, B Zhou, D Zhou, G Cheng, E Jiménez-Ruiz, A Soylu, ... European Semantic Web Conference, 123-128, 2022 | 16 | 2022 |
| Ontology reshaping for knowledge graph construction: applied on Bosch welding case D Zhou*, B Zhou*, Z Zheng, A Soylu, G Cheng, E Jimenez-Ruiz, ... International Semantic Web Conference, 770-790, 2022 | 16 | 2022 |
| Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding D Zhou*, B Zhou*, J Chen, G Cheng, E Kostylev, E Kharlamov The 10th International Joint Conference on Knowledge Graphs, 145-150, 2021 | 16 | 2021 |
| Machine learning aided phase retrieval algorithm for beam splitting with an LCoS-SLM D Mikhaylov, B Zhou, T Kiedrowski, R Mikut, AF Lasagni Laser Resonators, Microresonators, and Beam Control XXI 10904, 156-165, 2019 | 16 | 2019 |
| Machine Learning Methods for Product Quality Monitoring in Electric Resistance Welding B Zhou Institute for Automation and Applied Informatics (IAI), Karlsruhe Institute …, 2021 | 15 | 2021 |
| Executable knowledge graph for transparent machine learning in welding monitoring at Bosch Z Zheng, B Zhou, D Zhou, A Soylu, E Kharlamov Proceedings of the 31st ACM International Conference on Information …, 2022 | 14 | 2022 |
| SemML: Reusable ML for Condition Monitoring in Discrete Manufacturing Y Svetashova, B Zhou, S Schmid, T Pychinsky, E Kharlamov ISWC (Posters&Demos) 2721, 214, 2020 | 14 | 2020 |
Evgeny KharlamovBosch Center for Artificial IntelligenceEmail confirmado em de.bosch.com
