Pathologist-level interpretable whole-slide cancer diagnosis with deep learning Z Zhang, P Chen, M McGough, F Xing, C Wang, M Bui, Y Xie, M Sapkota, ... Nature Machine Intelligence 1 (5), 236-245, 2019 | 269 | 2019 |
Fully automatic knee osteoarthritis severity grading using deep neural networks with a novel ordinal loss P Chen, L Gao, X Shi, K Allen, L Yang Computerized Medical Imaging and Graphics 75, 84-92, 2019 | 191 | 2019 |
Efficient and robust cell detection: A structured regression approach Y Xie, F Xing, X Shi, X Kong, H Su, L Yang Medical image analysis 44, 245-254, 2018 | 138 | 2018 |
Face recognition by sparse discriminant analysis via joint L2, 1-norm minimization X Shi, Y Yang, Z Guo, Z Lai Pattern Recognition 47 (7), 2447-2453, 2014 | 133 | 2014 |
Loss-based attention for deep multiple instance learning X Shi, F Xing, Y Xie, Z Zhang, L Cui, L Yang Proceedings of the AAAI conference on artificial intelligence 34 (04), 5742-5749, 2020 | 97 | 2020 |
Pairwise based deep ranking hashing for histopathology image classification and retrieval X Shi, M Sapkota, F Xing, F Liu, L Cui, L Yang Pattern Recognition 81, 14-22, 2018 | 97 | 2018 |
Simple unsupervised graph representation learning Y Mo, L Peng, J Xu, X Shi, X Zhu Proceedings of the AAAI Conference on Artificial Intelligence 36 (7), 7797-7805, 2022 | 92 | 2022 |
A framework of joint graph embedding and sparse regression for dimensionality reduction X Shi, Z Guo, Z Lai, Y Yang, Z Bao, D Zhang IEEE Transactions on Image Processing 24 (4), 1341-1355, 2015 | 62 | 2015 |
Iterative attention mining for weakly supervised thoracic disease pattern localization in chest x-rays J Cai, L Lu, AP Harrison, X Shi, P Chen, L Yang Medical Image Computing and Computer Assisted Intervention–MICCAI 2018: 21st …, 2018 | 59 | 2018 |
Reverse graph learning for graph neural network L Peng, R Hu, F Kong, J Gan, Y Mo, X Shi, X Zhu IEEE transactions on neural networks and learning systems, 2022 | 56 | 2022 |
Kernel-based supervised discrete hashing for image retrieval X Shi, F Xing, J Cai, Z Zhang, Y Xie, L Yang Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 55 | 2016 |
Asymmetric discrete graph hashing X Shi, F Xing, K Xu, M Sapkota, L Yang Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 54 | 2017 |
Local and global consistency regularized mean teacher for semi-supervised nuclei classification H Su, X Shi, J Cai, L Yang International Conference on Medical Image Computing and Computer-Assisted …, 2019 | 53 | 2019 |
Are diffusion models vulnerable to membership inference attacks? J Duan, F Kong, S Wang, X Shi, K Xu International Conference on Machine Learning, 8717-8730, 2023 | 51 | 2023 |
Deep incomplete multi-view clustering via mining cluster complementarity J Xu, C Li, Y Ren, L Peng, Y Mo, X Shi, X Zhu Proceedings of the AAAI conference on artificial intelligence 36 (8), 8761-8769, 2022 | 51 | 2022 |
Graph temporal ensembling based semi-supervised convolutional neural network with noisy labels for histopathology image analysis X Shi, H Su, F Xing, Y Liang, G Qu, L Yang Medical image analysis 60, 101624, 2020 | 50 | 2020 |
Semicontour: A semi-supervised learning approach for contour detection Z Zhang, F Xing, X Shi, L Yang Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 47 | 2016 |
Two-dimensional whitening reconstruction for enhancing robustness of principal component analysis X Shi, Z Guo, F Nie, L Yang, J You, D Tao IEEE transactions on pattern analysis and machine intelligence 38 (10), 2130 …, 2015 | 46 | 2015 |
Robust principal component analysis via optimal mean by joint ℓ2, 1 and Schatten p-norms minimization X Shi, F Nie, Z Lai, Z Guo Neurocomputing 283, 205-213, 2018 | 45 | 2018 |
Deep convolutional hashing for low-dimensional binary embedding of histopathological images M Sapkota, X Shi, F Xing, L Yang IEEE journal of biomedical and health informatics 23 (2), 805-816, 2018 | 43 | 2018 |