| M3AE: Multimodal representation learning for brain tumor segmentation with missing modalities H Liu, D Wei, D Lu, J Sun, L Wang, Y Zheng Proceedings of the AAAI conference on artificial intelligence 37 (2), 1657-1665, 2023 | 37 | 2023 |
| Cost-driven scheduling of service processes in hybrid cloud with VM deployment and interval-based charging H Liang, Y Du, E Gao, J Sun Future Generation Computer Systems 107, 351-367, 2020 | 19 | 2020 |
| Unsupervised representation learning meets pseudo-label supervised self-distillation: A new approach to rare disease classification J Sun, D Wei, K Ma, L Wang, Y Zheng International Conference on Medical Image Computing and Computer-Assisted …, 2021 | 15 | 2021 |
| Lesion guided explainable few weak-shot medical report generation J Sun, D Wei, L Wang, Y Zheng International Conference on Medical Image Computing and Computer-Assisted …, 2022 | 12 | 2022 |
| Category-level regularized unlabeled-to-labeled learning for semi-supervised prostate segmentation with multi-site unlabeled data Z Xu, D Lu, J Yan, J Sun, J Luo, D Wei, S Frisken, Q Li, Y Zheng, RK Tong International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 6 | 2023 |
| Boost supervised pretraining for visual transfer learning: Implications of self-supervised contrastive representation learning J Sun, D Wei, K Ma, L Wang, Y Zheng Proceedings of the AAAI Conference on Artificial Intelligence 36 (2), 2307-2315, 2022 | 6 | 2022 |
| Federated modality-specific encoders and multimodal anchors for personalized brain tumor segmentation Q Dai, D Wei, H Liu, J Sun, L Wang, Y Zheng Proceedings of the AAAI Conference on Artificial Intelligence 38 (2), 1445-1453, 2024 | 5 | 2024 |
| You’ve got two teachers: Co-evolutionary image and report distillation for semi-supervised anatomical abnormality detection in chest x-ray J Sun, D Wei, Z Xu, D Lu, H Liu, L Wang, Y Zheng International Conference on Medical Image Computing and Computer-Assisted …, 2023 | 5 | 2023 |
| An interpretable imbalanced semi-supervised deep learning framework for improving differential diagnosis of skin diseases F Weng, Y Ma, J Sun, S Shan, Q Li, J Zhu, Y Wang, Y Xu arXiv preprint arXiv:2211.10858, 2022 | 2 | 2022 |
| Unlocking the Potential of Weakly Labeled Data: A Co-Evolutionary Learning Framework for Abnormality Detection and Report Generation J Sun, D Wei, Z Xu, D Lu, H Liu, H Wang, SA Tsaftaris, S McDonagh, ... IEEE Transactions on Medical Imaging, 2024 | | 2024 |
| FM-ABS: Promptable Foundation Model Drives Active Barely Supervised Learning for 3D Medical Image Segmentation Z Xu, C Chen, D Lu, J Sun, D Wei, Y Zheng, Q Li, RK Tong International Conference on Medical Image Computing and Computer-Assisted …, 2024 | | 2024 |
| Learning to Segment Multiple Organs from Multimodal Partially Labeled Datasets H Liu, D Wei, D Lu, J Sun, H Zheng, Y Zheng, L Wang International Conference on Medical Image Computing and Computer-Assisted …, 2024 | | 2024 |
| Hybrid unsupervised representation learning and pseudo-label supervised self-distillation for rare disease imaging phenotype classification with dispersion-aware imbalance … J Sun, D Wei, L Wang, Y Zheng Medical Image Analysis 93, 103102, 2024 | | 2024 |
Yefeng ZhengProfessor, Westlake University, Hangzhou, China, IEEE Fellow, AIMBE FellowE-mailová adresa ověřena na: westlake.edu.cn
