| Review of artificial intelligence techniques in imaging data acquisition, segmentation and diagnosis for covid-19 F Shi, J Wang, J Shi, Z Wu, Q Wang, Z Tang, K He, Y Shi, D Shen IEEE Reviews in Biomedical Engineering, 2020 | 1569 | 2020 |
| ST++: Make Self-training Work Better for Semi-supervised Semantic Segmentation L Yang, W Zhuo, L Qi, Y Shi, Y Gao IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 386 | 2022 |
| Ea-GANs: Edge-aware Generative Adversarial Networks for Cross-modality MR Image Synthesis B Yu, L Zhou, L Wang, Y Shi, J Fripp, P Bourgeat IEEE TMI, 2019 | 275 | 2019 |
| Revisiting weak-to-strong consistency in semi-supervised semantic segmentation L Yang, L Qi, L Feng, W Zhang, Y Shi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 248 | 2023 |
| A novel unsupervised camera-aware domain adaptation framework for person re-identification L Qi, L Wang, J Huo, L Zhou, Y Shi, Y Gao ICCV, 8080-8089, 2019 | 184 | 2019 |
| Inconsistency-aware uncertainty estimation for semi-supervised medical image segmentation Y Shi, J Zhang, T Ling, J Lu, Y Zheng, Q Yu, L Qi, Y Gao IEEE transactions on medical imaging 41 (3), 608-620, 2021 | 149 | 2021 |
| Mining latent classes for few-shot segmentation L Yang, W Zhuo, L Qi, Y Shi, Y Gao Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 148 | 2021 |
| Crossbar-net: A novel convolutional neural network for kidney tumor segmentation in ct images Q Yu, Y Shi, J Sun, Y Gao, J Zhu, Y Dai IEEE TIP 28 (8), 4060-4074, 2019 | 134 | 2019 |
| Machine Learning in Medical Imaging: 9th International Workshop, MLMI 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings Y Shi, HI Suk, M Liu Springer, 2018 | 112 | 2018 |
| Synergistic learning of lung lobe segmentation and hierarchical multi-instance classification for automated severity assessment of COVID-19 in CT images K He, W Zhao, X Xie, W Ji, M Liu, Z Tang, Y Shi, F Shi, Y Gao, J Liu, ... Pattern Recognition 113, 107828, 2021 | 107 | 2021 |
| Pelvic organ segmentation using distinctive curve guided fully convolutional networks K He, X Cao, Y Shi, D Nie, Y Gao, D Shen IEEE TMI 38 (2), 585-595, 2018 | 104 | 2018 |
| Real-time abnormal event detection in complicated scenes Y Shi, Y Gao, R Wang ICPR, 3653-3656, 2010 | 89 | 2010 |
| Webcaricature: a benchmark for caricature recognition J Huo, W Li, Y Shi, Y Gao, H Yin arXiv preprint arXiv:1703.03230, 2017 | 88 | 2017 |
| Differentiable meta-learning model for few-shot semantic segmentation P Tian, Z Wu, L Qi, L Wang, Y Shi, Y Gao Proceedings of the AAAI Conference on Artificial Intelligence 34 (07), 12087 …, 2020 | 86 | 2020 |
| Asymmetric distribution measure for few-shot learning W Li, L Wang, J Huo, Y Shi, Y Gao, J Luo arXiv preprint arXiv:2002.00153, 2020 | 80 | 2020 |
| Deep Symmetric Adaptation Network for Cross-modality Medical Image Segmentation X Han, L Qi, Q Yu, Z Zhou, Y Zheng, Y Shi, Y Gao IEEE Transactions on Medical Imaging, 2021 | 77 | 2021 |
| Maskreid: A mask based deep ranking neural network for person re-identification L Qi, J Huo, L Wang, Y Shi, Y Gao arXiv preprint arXiv:1804.03864, 2018 | 75 | 2018 |
| Generalizable Cross-modality Medical Image Segmentation via Style Augmentation and Dual Normalization Z Zhou, L Qi, X Yang, D Ni, Y Shi IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 | 72 | 2022 |
| Libfewshot: A comprehensive library for few-shot learning W Li, Z Wang, X Yang, C Dong, P Tian, T Qin, J Huo, Y Shi, L Wang, ... IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023 | 67 | 2023 |
| MRM-lasso: A sparse multiview feature selection method via low-rank analysis W Yang, Y Gao, Y Shi, L Cao IEEE TNNLS 26 (11), 2801-2815, 2015 | 64 | 2015 |
