| Can potential defects in LPBF be healed from the laser exposure of subsequent layers? A quantitative study A Ulbricht, G Mohr, SJ Altenburg, S Oster, C Maierhofer, G Bruno Metals 11 (7), 1012, 2021 | 23 | 2021 |
| A deep learning framework for defect prediction based on thermographic in-situ monitoring in laser powder bed fusion S Oster, PP Breese, A Ulbricht, G Mohr, SJ Altenburg Journal of Intelligent Manufacturing 35 (4), 1687-1706, 2024 | 12 | 2024 |
| On the registration of thermographic in situ monitoring data and computed tomography reference data in the scope of defect prediction in laser powder bed fusion S Oster, T Fritsch, A Ulbricht, G Mohr, G Bruno, C Maierhofer, ... Metals 12 (6), 947, 2022 | 11 | 2022 |
| Investigation of the thermal history of L-PBF metal parts by feature extraction from in-situ SWIR thermography S Oster, C Maierhofer, G Mohr, K Hilgenberg, A Ulbricht, SJ Altenburg Thermosense: Thermal Infrared Applications XLIII 11743, 84-94, 2021 | 4 | 2021 |
| Potentials and challenges of deep-learningassisted porosity prediction based on thermographic in situ monitoring in laser powder bed fusion: Potentiale und Herausforderungen in … S Oster, N Scheuschner, K Chand, SJ Altenburg, G Gerlach tm-Technisches Messen 90 (s1), 85-96, 2023 | 1 | 2023 |
| Aktive Laserthermografie im L-PBF-Prozess zur in-situ Detektion von Defekten PP Breese, T Becker, S Oster, SJ Altenburg, C Metz, C Maierhofer DGZfP-Berichtsband 177, 1-9, 2022 | 1 | 2022 |
| Erratum to: Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion S Oster, N Scheuschner, K Chand, SJ Altenburg, G Gerlach tm-Technisches Messen 91 (2), 139-141, 2024 | | 2024 |
| Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in laser powder bed fusion (vol 90, pg 85, 2023) S Oster, N Scheuschner, K Chand, SJ Altenburg, G Gerlach TM-TECHNISCHES MESSEN, 2024 | | 2024 |
| C5. 4-From Thermographic In-situ Monitoring to Porosity Detection-A Deep Learning Framework for Quality Control in Laser Powder Bed Fusion S Oster, N Scheuschner, K Chand, P Breese, T Becker, S Altenburg, ... Lectures, 179-180, 2023 | | 2023 |
| In-situ defect detection for laser powder bed fusion with active laser thermography PP Breese | | 2023 |
| Potentials and challenges of deep-learning-assisted porosity prediction based on thermographic in-situ monitoring in PBF-LB/M S Oster | | 2023 |
| In-situ monitoring of the laser powder bed fusion process by thermography, optical tomography and melt pool monitoring for defect detection N Scheuschner, F Heinrichsdorff, S Oster, E Uhlmann, J Polte, A Gordei, ... Lasers in Manufacturing Conference 2023, 1-10, 2023 | | 2023 |
| In-situ defect detection via active laser thermographic testing for PBF-LB/M PP Breese, T Becker, S Oster, C Metz, S Altenburg LiM 2023 Proceedings, 1-10, 2023 | | 2023 |
| In-situ Prüfung additiv gefertigter L-PBF-Bauteile mit aktiver Laserthermografie PP Breese, T BECKER, S OSTER, C METZ, SJ ALTENBURG | | 2022 |
| Machine Learning based defect detection in Laser Powder Bed Fusion utilizing thermographic feature data S Oster | | 2022 |
| Defect prediction on the Base of Thermographic features in Laser Powder Bed Fusion Utilizing Machine Learning Algorithms S Oster | | 2022 |
| Porosity prediction in metal based additive manufacturing utilizing in situ thermography S Oster | | 2022 |
| Defect prediction in laser powder bed fusion based on thermographic features utilizing convolutional neural networks S Oster | | 2022 |
| Multispectral in-situ monitoring of a L-PBF manufacturing process using three thermographic camera systems S Oster | | 2021 |
| Can Potential Defects in LPBF Be Healed from the Laser Exposure of Subsequent Layers? A Quantitative Study. Metals 2021, 11, 1012 A Ulbricht, G Mohr, SJ Altenburg, S Oster, C Maierhofer, G Bruno s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2021 | | 2021 |
