| Application of supervised machine learning for defect detection during metallic powder bed fusion additive manufacturing using high resolution imaging. C Gobert, EW Reutzel, J Petrich, AR Nassar, S Phoha Additive Manufacturing 21, 517-528, 2018 | 457 | 2018 |
| Porosity segmentation in X-ray computed tomography scans of metal additively manufactured specimens with machine learning C Gobert, A Kudzal, J Sietins, C Mock, J Sun, B McWilliams Additive Manufacturing 36, 101460, 2020 | 55 | 2020 |
| Machine learning for defect detection for PBFAM using high resolution layerwise imaging coupled with post-build CT scans J Petrich, C Gobert, S Phoha, AR Nassar, EW Reutzel University of Texas at Austin, 2017 | 47 | 2017 |
| Process qualification of laser powder bed fusion based on processing-defect structure-fatigue properties in Ti-6Al-4V SP Narra, AD Rollett, A Ngo, D Scannapieco, M Shahabi, T Reddy, ... Journal of Materials Processing Technology 311, 117775, 2023 | 21 | 2023 |
| Application of supervised machine learning for defect detection during metallic powder bed fusion additive manufacturing using high resolution imaging, Addit. Manuf. 21 (2018 … C Gobert, EW Reutzel, J Petrich, AR Nassar, S Phoha | 19 | |
| Where is the machine looking? Locating discriminative light-scattering features by class-activation mapping P Piedra, C Gobert, A Kalume, YL Pan, M Kocifaj, K Muinonen, A Penttilä, ... Journal of Quantitative Spectroscopy and Radiative Transfer 247, 106936, 2020 | 12 | 2020 |
| Conditional generative adversarial networks for in-situ layerwise additive manufacturing data C Gobert, E Arrieta, A Belmontes, BR Wicker, F Medina, B McWilliams Proceeding of the 29th international Solid Freeform Fabrication Symposium, 2019 | 11 | 2019 |
| Inference of highly time-resolved melt pool visual characteristics and spatially-dependent lack-of-fusion defects in laser powder bed fusion using acoustic and thermal emission … H Liu, C Gobert, K Ferguson, B Abranovic, H Chen, JL Beuth, AD Rollett, ... Additive Manufacturing 83, 104057, 2024 | 3 | 2024 |
| Online discontinuity detection in metallic powder bed fusion additive manufacturing processes using visual inspection sensors and supervised machine learning CJ Gobert | 3 | 2017 |
| Inference of Highly Time-resolved Melt Pool Visual Characteristics in Laser Powder Bed Fusion from Acoustic and Thermal Emission Data H Liu, C Gobert, K Ferguson, B Abranovic, H Chen, JL Beuth, AD Rollett, ... arXiv preprint arXiv:2310.05289, 2023 | 1 | 2023 |
| Fatigue-based process window for laser beam powder bed fusion additive manufacturing T Reddy, A Ngo, JP Miner, C Gobert, JL Beuth, AD Rollett, ... International Journal of Fatigue, 108428, 2024 | | 2024 |
| Process Development in Laser Powder Bed Fusion at the Melt Pool Scale C Gobert Carnegie Mellon University, 2023 | | 2023 |
