| Decoupled appearance and motion learning for efficient anomaly detection in surveillance video B Li, S Leroux, P Simoens Computer Vision and Image Understanding 210, 103249, 2021 | 30 | 2021 |
| Partial variance reduction improves non-convex federated learning on heterogeneous data B Li, MN Schmidt, TS Alstrøm, SU Stich arXiv preprint arXiv:2212.02191, 2022 | 19* | 2022 |
| On uncertainty estimation in active learning for image segmentation B Li, TS Alstrøm arXiv preprint arXiv:2007.06364, 2020 | 18 | 2020 |
| Multi-branch neural networks for video anomaly detection in adverse lighting and weather conditions S Leroux, B Li, P Simoens Proceedings of the IEEE/CVF Winter Conference on Applications of Computer …, 2022 | 16 | 2022 |
| Raman spectrum matching with contrastive representation learning B Li, MN Schmidt, TS Alstrøm Analyst 147 (10), 2238-2246, 2022 | 8 | 2022 |
| Automated training of location-specific edge models for traffic counting S Leroux, B Li, P Simoens Computers and Electrical Engineering 99, 107763, 2022 | 5 | 2022 |
| Nitroaromatic explosives’ detection and quantification using an attention-based transformer on surface-enhanced Raman spectroscopy maps B Li, G Zappalá, E Dumont, A Boisen, T Rindzevicius, MN Schmidt, ... Analyst 148 (19), 4787-4798, 2023 | 1 | 2023 |
| An improved analysis of per-sample and per-update clipping in federated learning B Li, X Jiang, MN Schmidt, TS Alstrøm, SU Stich The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Synthetic data shuffling accelerates the convergence of federated learning under data heterogeneity B Li, Y Esfandiari, MN Schmidt, TS Alstrøm, SU Stich arXiv preprint arXiv:2306.13263, 2023 | | 2023 |
