| Normality learning in multispace for video anomaly detection Y Zhang, X Nie, R He, M Chen, Y Yin IEEE Transactions on Circuits and Systems for Video Technology 31 (9), 3694-3706, 2020 | 79 | 2020 |
| Safe-student for safe deep semi-supervised learning with unseen-class unlabeled data R He, Z Han, X Lu, Y Yin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 30 | 2022 |
| Not all parameters should be treated equally: Deep safe semi-supervised learning under class distribution mismatch R He, Z Han, Y Yang, Y Yin Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 6874-6883, 2022 | 22 | 2022 |
| RONF: reliable outlier synthesis under noisy feature space for out-of-distribution detection R He, Z Han, X Lu, Y Yin Proceedings of the 30th ACM International Conference on Multimedia, 4242-4251, 2022 | 9 | 2022 |
| Semi-supervised screening of covid-19 from positive and unlabeled data with constraint non-negative risk estimator Z Han, R He, T Li, B Wei, J Wang, Y Yin Information Processing in Medical Imaging: 27th International Conference …, 2021 | 8 | 2021 |
| Discriminability and transferability estimation: a bayesian source importance estimation approach for multi-source-free domain adaptation Z Han, Z Zhang, F Wang, R He, W Su, X Xi, Y Yin Proceedings of the AAAI Conference on Artificial Intelligence 37 (6), 7811-7820, 2023 | 6 | 2023 |
| Mhpl: Minimum happy points learning for active source free domain adaptation F Wang, Z Han, Z Zhang, R He, Y Yin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 6 | 2023 |
| Towards safe and robust weakly-supervised anomaly detection under subpopulation shift R He, Z Han, Y Yin Knowledge-Based Systems 250, 109088, 2022 | 6 | 2022 |
| Neighborhood-based credibility anchor learning for universal domain adaptation W Su, Z Han, R He, B Wei, X He, Y Yin Pattern Recognition 142, 109686, 2023 | 5 | 2023 |
| Topological structure learning for weakly-supervised out-of-distribution detection R He, R Li, Z Han, X Yang, Y Yin Proceedings of the 31st ACM International Conference on Multimedia, 4858-4866, 2023 | 3 | 2023 |
| Robust anomaly detection from partially observed anomalies with augmented classes R He, Z Han, Y Zhang, X He, X Nie, Y Yin Artificial Intelligence: First CAAI International Conference, CICAI 2021 …, 2021 | 3 | 2021 |
| How well does gpt-4v (ision) adapt to distribution shifts? a preliminary investigation Z Han, G Zhou, R He, J Wang, X Xie, T Wu, Y Yin, S Khan, L Yao, T Liu, ... arXiv preprint arXiv:2312.07424, 2023 | 2 | 2023 |
| SNAIL: Semi-Separated Uncertainty Adversarial Learning for Universal Domain Adaptation Z Han, W Su, R He, Y Yin Asian Conference on Machine Learning, 436-451, 2023 | 2 | 2023 |
| CLIP-driven Outliers Synthesis for few-shot OOD detection H Sun, R He, Z Han, Z Lin, Y Gong, Y Yin arXiv preprint arXiv:2404.00323, 2024 | | 2024 |
| Exploring Channel-Aware Typical Features for Out-of-Distribution Detection R He, Y Yuan, Z Han, F Wang, W Su, Y Yin, T Liu, Y Gong Proceedings of the AAAI Conference on Artificial Intelligence 38 (11), 12402 …, 2024 | | 2024 |
| Learning sample-aware threshold for semi-supervised learning Q Wei, L Feng, H Sun, R Wang, R He, Y Yin Machine Learning, 1-23, 2024 | | 2024 |
| LHAct: Rectifying Extremely Low and High Activations for Out-of-Distribution Detection Y Yuan, R He, Z Han, Y Yin Proceedings of the 31st ACM International Conference on Multimedia, 8105-8113, 2023 | | 2023 |
Zhongyi HanKing Abdullah University of Science and TechnologyZweryfikowany adres z kaust.edu.sa
