Xiaobin Hu
Xiaobin Hu
Tencent Youtu Lab;Technische Universität München (TUM)
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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
Knowledge-aided convolutional neural network for small organ segmentation
Y Zhao, H Li, S Wan, A Sekuboyina, X Hu, G Tetteh, M Piraud, B Menze
IEEE journal of biomedical and health informatics 23 (4), 1363-1373, 2019
Ultra-high-definition image dehazing via multi-guided bilateral learning
Z Zheng, W Ren, X Cao, X Hu, T Wang, F Song, X Jia
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR …, 2021
Highly accurate dichotomous image segmentation
X Qin, H Dai, X Hu, DP Fan, L Shao, L Van Gool
European Conference on Computer Vision, 38-56, 2022
Face Super-Resolution Guided by 3D Facial Priors
X Hu, W Ren, J LaMaster, X Cao, X Li, Z Li, B Menze, W Liu
European Conference on Computer Vision (Spotlight paper), 763-780, 2020
High-resolution Iterative Feedback Network for Camouflaged Object Detection
X Hu, S Wang, X Qin, H Dai, W Ren, D Luo, Y Tai, L Shao
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 23), 2022
Stochastic analysis using the generalized perturbation stable node-based smoothed finite element method
XB Hu, XY Cui, H Feng, GY Li
Engineering Analysis with Boundary Elements 70, 40-55, 2016
SRGAT: Single image super-resolution with graph attention network
Y Yan, W Ren, X Hu, K Li, H Shen, X Cao
IEEE Transactions on Image Processing 30, 4905-4918, 2021
Coarse-to-fine adversarial networks and zone-based uncertainty analysis for NK/T-cell lymphoma segmentation in CT/PET images
X Hu, R Guo, J Chen, H Li, D Waldmannstetter, Y Zhao, B Li, K Shi, ...
IEEE journal of biomedical and health informatics 24 (9), 2599-2608, 2020
A Copula-based perturbation stochastic method for fiber-reinforced composite structures with correlations
XY Cui, XB Hu, Y Zeng
Computer Methods in Applied Mechanics and Engineering 322, 351-372, 2017
Pyramid Architecture Search for Real-time Image Deblurring
X Hu, W Ren, K Yu, K Zhang, X Cao, W Liu, B Menze
International Conference on Computer Vision (ICCV 2021), 2021
Isogeometric generalized n th order perturbation-based stochastic method for exact geometric modeling of (composite) structures: Static and dynamic analysis with random …
C Ding, X Hu, X Cui, G Li, Y Cai, KK Tamma
Computer Methods in Applied Mechanics and Engineering 346, 1002-1024, 2019
Weakly supervised deep learning for determining the prognostic value of 18 F-FDG PET/CT in extranodal natural killer/T cell lymphoma, nasal type
R Guo, X Hu, H Song, P Xu, H Xu, A Rominger, X Lin, B Menze, B Li, ...
European Journal of Nuclear Medicine and Molecular Imaging, 1-11, 2021
The performance prediction and optimization of the fiber-reinforced composite structure with uncertain parameters
XB Hu, XY Cui, ZM Liang, GY Li
Composite Structures 164, 207-218, 2017
Hierarchical multi-class segmentation of glioma images using networks with multi-level activation function
X Hu, H Li, Y Zhao, C Dong, BH Menze, M Piraud
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
A modified smoothed finite element method for static and free vibration analysis of solid mechanics
XY Cui, XB Hu, GY Li, GR Liu
International Journal of Computational Methods 13 (06), 1650043, 2016
Feedback graph attention convolutional network for MR images enhancement by exploring self-similarity features
X Hu, Y Yan, W Ren, H Li, A Bayat, Y Zhao, B Menze
Medical Imaging with Deep Learning, 327-337, 2021
Face Restoration via Plug-and-Play 3D Facial Priors
X Hu, W Ren, J Yang, X Cao, D Wipf, B Menze, X Tong, H Zha
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021
Morphological residual convolutional neural network (M-RCNN) for intelligent recognition of wear particles from artificial joints
X Hu, J Song, Z Liao, Y Liu, J Gao, B Menze, W Liu
Friction 10 (4), 560-572, 2022
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