| Modeling the temperature of hot rolled steel plate with semi-supervised learning methods H Tiensuu, I Juutilainen, J Röning Discovery Science: 14th International Conference, DS 2011, Espoo, Finland …, 2011 | 8 | 2011 |
| An online quality monitoring tool for information acquisition and sharing in manufacturing: requirements and solutions for the steel industry S Tamminen, E Ferreira, H Tiensuu, H Helaakoski, V Kyllönen, J Jokisaari, ... International Journal of Industrial and Systems Engineering 33 (3), 291-313, 2019 | 7 | 2019 |
| From measurements to knowledge-online quality monitoring and smart manufacturing S Tamminen, H Tiensuu, E Ferreira, H Helaakoski, V Kyllönen, J Jokisaari, ... Advances in Data Mining. Applications and Theoretical Aspects: 18th …, 2018 | 7 | 2018 |
| Evidence-based and explainable smart decision support for quality improvement in stainless steel manufacturing H Tiensuu, S Tamminen, E Puukko, J Röning Applied Sciences 11 (22), 10897, 2021 | 6 | 2021 |
| Ai enhanced alarm presentation for quality monitoring S Tamminen, X Liu, H Tiensuu, E Ferreira, E Puukko, J Röning 2018 IEEE International Conference on Internet of Things (iThings) and IEEE …, 2018 | 4 | 2018 |
| Automatic recognition of steel plate side edge shape using classification and regression models P Siirtola, S Tamminen, E Ferreira, H Tiensuu, E Prokkola, J Röning Proceedings of the 9th Eurosim Congress on Modelling and Simulation (EUROSIM …, 2016 | 4 | 2016 |
| Data center for biomass drying M Vesterlund, S Borisová, E Lundmark, V Leinonen, H Tiensuu, ... | 2 | 2021 |
| Recognizing steel plate side edge shape automatically using classification and regression models P Siirtola, S Tamminen, E Ferreira, H Tiensuu, E Prokkola, J Röning Proceedings of The 9th EUROSIM Congress on Modelling and Simulation, EUROSIM …, 2018 | 2 | 2018 |
| Intelligent methods for root cause analysis behind the center line deviation of the steel strip H Tiensuu, S Tamminen, O Haapala, J Röning Open Engineering 10 (1), 386-393, 2020 | 1 | 2020 |
| Improving the yield of steel plates by updating the slab design with statistical models H Tiensuu, S Tamminen, A Pikkuaho, J Röning Ironmaking & Steelmaking 44 (8), 577-586, 2017 | 1 | 2017 |
| Steel property and process models for quality control and optimization S Tamminen, H Tiensuu, I Juutilainen, J Röning Materials Science Forum 762, 301-306, 2013 | 1 | 2013 |
| Smart system for distributed sensing J Roning, J Haverinen, A Kemppainen, H Morsari, I Vallivaara 2008 11th International Biennial Baltic Electronics Conference, 21-30, 2008 | 1 | 2008 |
| Modeling intrinsic factors of inclusive engagement in citizen science: Insights from the participants’ survey analysis of CSI-COP S Hadad, M Zhitomirsky-Geffet, H Shah, D Rigler, U Celentano, H Tiensuu, ... Plos one 18 (11), e0294575, 2023 | | 2023 |
| Road conditions analysis and forecasting in Arctic: multi-source machine learning approach J Suutala, M Malin, H Tiensuu, S Tamminen XXVIII General Assembly of the International Union of Geodesy and Geophysics …, 2023 | | 2023 |
| Modelling the quality of the steel products under challenging measurement conditions H Tiensuu University of Oulu, 2022 | | 2022 |
| Online quality monitoring tool H Helaakoski, V Kyllönen, S Tamminen, H Tiensuu, E Ferreira, J Jokisaari, ... SIMP-System Integrated Metals Processing: Final report 4/2017, 144, 2017 | | 2017 |
| Advanced quality monitoring methods for steel production S Louhenkilpi, J Miettinen, J Laine, I Juutilainen, P Laurinen, M Häkkinen, ... SIMP-System Integrated Metals Processing: Final report 4/2017, 91-120, 2017 | | 2017 |
