Semi-supervised contrastive learning for label-efficient medical image segmentation X Hu, D Zeng, X Xu, Y Shi MICCAI 2021, 2021 | 98 | 2021 |
Positional Contrastive Learning for Volumetric Medical Image Segmentation D Zeng, Y Wu, X Hu, X Xu, H Yuan, M Huang, J Zhuang, J Hu, Y Shi MICCAI 2021, 2021 | 89 | 2021 |
Federated contrastive learning for volumetric medical image segmentation Y Wu, D Zeng, Z Wang, Y Shi, J Hu MICCAI 2021, 2021 | 59 | 2021 |
Fairprune: Achieving fairness through pruning for dermatological disease diagnosis Y Wu, D Zeng, X Xu, Y Shi, J Hu MICCAI 2022, 743-753, 2022 | 43 | 2022 |
Distributed contrastive learning for medical image segmentation Y Wu, D Zeng, Z Wang, Y Shi, J Hu Medical Image Analysis 81, 102564, 2022 | 36 | 2022 |
Federated contrastive learning for dermatological disease diagnosis via on-device learning Y Wu, D Zeng, Z Wang, Y Sheng, L Yang, AJ James, Y Shi, J Hu 2021 IEEE/ACM International Conference On Computer Aided Design (ICCAD), 1-7, 2021 | 22 | 2021 |
Decentralized unsupervised learning of visual representations Y Wu, Z Wang, D Zeng, M Li, Y Shi, J Hu arXiv preprint arXiv:2111.10763, 2021 | 21 | 2021 |
Enabling on-device self-supervised contrastive learning with selective data contrast Y Wu, Z Wang, D Zeng, Y Shi, J Hu DAC 2021, 2021 | 19 | 2021 |
Mda: A reconfigurable memristor-based distance accelerator for time series mining on data centers X Xu, F Lin, W Xu, X Yao, Y Shi, D Zeng, Y Hu TCAD 38 (5), 785-797, 2018 | 15 | 2018 |
A deep learning approach with temporal consistency for automatic myocardial segmentation of quantitative myocardial contrast echocardiography M Li, D Zeng, Q Xie, R Xu, Y Wang, D Ma, Y Shi, X Xu, M Huang, H Fei The International Journal of Cardiovascular Imaging 37 (6), 1967-1978, 2021 | 12 | 2021 |
Federated contrastive learning for dermatological disease diagnosis via on-device learning. In 2021 IEEE Y Wu, D Zeng, Z Wang, Y Sheng, L Yang, AJ James, Y Shi, J Hu ACM International Conference On Computer Aided Design (ICCAD), 1-7, 0 | 12 | |
An efficient memristor-based distance accelerator for time series data mining on data centers X Xu, D Zeng, W Xu, Y Shi, Y Hu DAC 2017, 2017 | 11 | 2017 |
Synthetic data can also teach: Synthesizing effective data for unsupervised visual representation learning Y Wu, Z Wang, D Zeng, Y Shi, J Hu Proceedings of the AAAI Conference on Artificial Intelligence 37 (3), 2866-2874, 2023 | 9 | 2023 |
Segmentation with multiple acceptable annotations: A case study of myocardial segmentation in contrast echocardiography D Zeng, M Li, Y Ding, X Xu, Q Xie, R Xu, H Fei, M Huang, J Zhuang, Y Shi Information Processing in Medical Imaging: 27th International Conference …, 2021 | 9 | 2021 |
Towards cardiac intervention assistance: hardware-aware neural architecture exploration for real-time 3D cardiac cine MRI segmentation D Zeng, W Jiang, T Wang, X Xu, H Yuan, M Huang, J Zhuang, J Hu, Y Shi Proceedings of the 39th International Conference on Computer-Aided Design, 1-8, 2020 | 9 | 2020 |
Prediction of pulmonary pressure after Glenn shunts by computed tomography–based machine learning models L Huang, J Li, M Huang, J Zhuang, H Yuan, Q Jia, D Zeng, L Que, Y Xi, ... European radiology 30, 1369-1377, 2020 | 9 | 2020 |
Federated self-supervised contrastive learning and masked autoencoder for dermatological disease diagnosis Y Wu, D Zeng, Z Wang, Y Sheng, L Yang, AJ James, Y Shi, J Hu arXiv preprint arXiv:2208.11278, 2022 | 8 | 2022 |
Accurate congenital heart disease model generation for 3d printing X Xu, T Wang, D Zeng, Y Shi, Q Jia, H Yuan, M Huang, J Zhuang 2019 IEEE International Workshop on Signal Processing Systems (SiPS), 127-130, 2019 | 8 | 2019 |
Learning to skip for language modeling D Zeng, N Du, T Wang, Y Xu, T Lei, Z Chen, C Cui arXiv preprint arXiv:2311.15436, 2023 | 5 | 2023 |
Myocardial segmentation of cardiac MRI sequences with temporal consistency for coronary artery disease diagnosis Y Chen, W Xie, J Zhang, H Qiu, D Zeng, Y Shi, H Yuan, J Zhuang, Q Jia, ... Frontiers in Cardiovascular Medicine 9, 804442, 2022 | 4 | 2022 |