| Graph Neural Networks based Log Anomaly Detection and Explanation Z Li, J Shi, M Van Leeuwen Proceedings of the 2024 IEEE/ACM 46th International Conference on Software …, 2024 | 20 | 2024 |
| Spectral reconstruction and disparity from spatio-spectrally coded light fields via multi-task deep learning M Schambach, J Shi, M Heizmann 2021 International Conference on 3D Vision (3DV), 186-196, 2021 | 5 | 2021 |
| Multi-stage Deep Learning Artifact Reduction for Parallel-beam Computed Tomography J Shi, DM Pelt, KJ Batenburg Journal of Synchrotron Radiation, 2025 | 3* | 2025 |
| LoDoInd: Introducing A Benchmark Low-dose Industrial CT Dataset and Enhancing Denoising with 2.5 D Deep Learning Techniques J Shi, O Elkilany, A Fischer, A Suppes, DM Pelt, KJ Batenburg International Conference on Industrial Computed Tomography, 2024 | 3 | 2024 |
| SR4ZCT: Self-supervised Through-Plane Resolution Enhancement for CT Images with Arbitrary Resolution and Overlap J Shi, DM Pelt, KJ Batenburg International Workshop on Machine Learning in Medical Imaging, 52-61, 2023 | 3 | 2023 |
| Cross-domain graph level anomaly detection Z Li, S Liang, J Shi, M van Leeuwen IEEE Transactions on Knowledge and Data Engineering, 2024 | 1 | 2024 |
| Implicit Neural Representations for Robust Joint Sparse-View CT Reconstruction J Shi, J Zhu, DM Pelt, KJ Batenburg, MB Blaschko Transactions on Machine Learning Research, 2024 | 1 | 2024 |
| Self-supervised resolution enhancement for anisotropic volumes in edge illumination X-ray phase contrast micro-computed tomography J Shi, L Brown, AR Zekavat, DM Pelt, CK Hagen Tomography of Materials and Structures 7, 100046, 2025 | | 2025 |
| A Comparative Study of Supervised and Self-Supervised Denoising Techniques for Defect Segmentation in Industrial CT Imaging V Florian, J Shi, WJ Palenstijn, DM Pelt, KJ Batenburg, T Lang, C Heinzl, ... | | 2025 |
