Xiaoshuang Shi
Xiaoshuang Shi
University of Electronic Science and Technology of China
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Citado por
Citado por
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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
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