| MMSegmentation: Openmmlab semantic segmentation toolbox and benchmark MMS Contributors | 937 | 2020 |
| Vision transformer adapter for dense predictions Z Chen, Y Duan, W Wang, J He, T Lu, J Dai, Y Qiao arXiv preprint arXiv:2205.08534, 2022 | 654 | 2022 |
| Adaptive pyramid context network for semantic segmentation J He, Z Deng, L Zhou, Y Wang, Y Qiao Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 445 | 2019 |
| Dynamic multi-scale filters for semantic segmentation J He, Z Deng, Y Qiao Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 338 | 2019 |
| Attention-driven dynamic graph convolutional network for multi-label image recognition J Ye, J He, X Peng, W Wu, Y Qiao Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 245 | 2020 |
| Sam-med2d J Cheng, J Ye, Z Deng, J Chen, T Li, H Wang, Y Su, Z Huang, J Chen, ... arXiv preprint arXiv:2308.16184, 2023 | 180 | 2023 |
| Unleashing the strengths of unlabeled data in pan-cancer abdominal organ quantification: the flare22 challenge J Ma, Y Zhang, S Gu, C Ge, S Ma, A Young, C Zhu, K Meng, X Yang, ... arXiv preprint arXiv:2308.05862, 2023 | 131 | 2023 |
| Sphinx-x: Scaling data and parameters for a family of multi-modal large language models D Liu, R Zhang, L Qiu, S Huang, W Lin, S Zhao, S Geng, Z Lin, P Jin, ... arXiv preprint arXiv:2402.05935, 2024 | 108 | 2024 |
| Self pre-training with masked autoencoders for medical image classification and segmentation L Zhou, H Liu, J Bae, J He, D Samaras, P Prasanna 2023 IEEE 20th International Symposium on Biomedical Imaging (ISBI), 1-6, 2023 | 89 | 2023 |
| Tensor low-rank reconstruction for semantic segmentation W Chen, X Zhu, R Sun, J He, R Li, X Shen, B Yu Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 86 | 2020 |
| Multi-label ocular disease classification with a dense correlation deep neural network J He, C Li, J Ye, Y Qiao, L Gu Biomedical Signal Processing and Control 63, 102167, 2021 | 85 | 2021 |
| Self pre-training with masked autoencoders for medical image analysis L Zhou, H Liu, J Bae, J He, D Samaras, P Prasanna arXiv preprint arXiv:2203.05573 1 (3), 2022 | 80 | 2022 |
| Stu-net: Scalable and transferable medical image segmentation models empowered by large-scale supervised pre-training Z Huang, H Wang, Z Deng, J Ye, Y Su, H Sun, J He, Y Gu, L Gu, S Zhang, ... arXiv preprint arXiv:2304.06716, 2023 | 78 | 2023 |
| Development and clinical deployment of a smartphone-based visual field deep learning system for glaucoma detection F Li, D Song, H Chen, J Xiong, X Li, H Zhong, G Tang, S Fan, DSC Lam, ... NPJ digital medicine 3 (1), 123, 2020 | 72 | 2020 |
| EfficientFCN: Holistically-guided decoding for semantic segmentation J Liu, J He, J Zhang, JS Ren, H Li Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23 …, 2020 | 71 | 2020 |
| Multimodal machine learning using visual fields and peripapillary circular OCT scans in detection of glaucomatous optic neuropathy J Xiong, F Li, D Song, G Tang, J He, K Gao, H Zhang, W Cheng, Y Song, ... Ophthalmology 129 (2), 171-180, 2022 | 69 | 2022 |
| Prostate segmentation using 2D bridged U-net W Chen, Y Zhang, J He, Y Qiao, Y Chen, H Shi, EX Wu, X Tang 2019 International Joint Conference on Neural Networks (IJCNN), 1-7, 2019 | 66 | 2019 |
| Revisiting nnu-net for iterative pseudo labeling and efficient sliding window inference Z Huang, H Wang, J Ye, J Niu, C Tu, Y Yang, S Du, Z Deng, L Gu, J He MICCAI Challenge on Fast and Low-Resource Semi-supervised Abdominal Organ …, 2022 | 59 | 2022 |
| The autopet challenge: towards fully automated lesion segmentation in oncologic PET/CT imaging S Gatidis, M Früh, M Fabritius, S Gu, K Nikolaou, C La Fougère, J Ye, J He, ... | 57 | 2023 |
| Deep relation transformer for diagnosing glaucoma with optical coherence tomography and visual field function D Song, B Fu, F Li, J Xiong, J He, X Zhang, Y Qiao IEEE Transactions on Medical Imaging 40 (9), 2392-2402, 2021 | 55 | 2021 |
