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Xianliang Hu
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2020 – today
- 2023
- [j20]Chang Liu, Xianliang Hu
:
Deep neural network with deformable convolution and side window convolution for image denoising. Pattern Recognit. Lett. 171: 92-98 (2023) - [j19]Qi Bai
Quantity study on a novel quantum neural network with alternately controlled gates for binary image classification. Quantum Inf. Process. 22(5): 184 (2023) - 2022
- [j18]Yixin Li, Xianliang Hu:
Artificial neural network approximations of Cauchy inverse problem for linear PDEs. Appl. Math. Comput. 414: 126678 (2022) - [j17]Dingding Yu
A two-scaled fully convolutional learning network for road detection. IET Image Process. 16(4): 948-957 (2022) - [j16]Dingding Yu, Xianliang Hu, Kewei Liang
A parallel algorithm for multi-AGV systems. J. Ambient Intell. Humaniz. Comput. 13(4): 2309-2323 (2022) - [j15]Haiying Zhou, Qi Bai
Deep CTS: a Deep Neural Network for Identification MRI of Carpal Tunnel Syndrome. J. Digit. Imaging 35(6): 1433-1444 (2022) - [j14]Jinyue Chen, Silu Chen, Xianliang Hu
Image segmentation by phase-field models with local information. Multim. Tools Appl. 81(2): 3039-3057 (2022) - 2021
- [j13]Jinyue Chen, Yixin Li, Xianliang Hu:
A two-grid method for the phase-field model of photonic band gap optimization. Comput. Math. Appl. 96: 44-54 (2021) - [j12]Yixin Li, Bangjian Zhou, Xianliang Hu:
A two-grid method for level-set based topology optimization with GPU-acceleration. J. Comput. Appl. Math. 389: 113336 (2021) - 2020
- [j11]Dingding Yu, Kaijie Zhang
Detection of peripherally inserted central catheter (PICC) in chest X-ray images: A multi-task deep learning model. Comput. Methods Programs Biomed. 197: 105674 (2020) - [j10]Shengfeng Zhu, Xianliang Hu
On accuracy of approximate boundary and distributed H1 shape gradient flows for eigenvalue optimization. J. Comput. Appl. Math. 365 (2020) - [i1]Yixin Li, Xianliang Hu:
An artificial neural network approximation for Cauchy inverse problems. CoRR abs/2001.01413 (2020)
2010 – 2019
- 2019
- [j9]Futuan Li, Xianliang Hu:
A phase-field method for shape optimization of incompressible flows. Comput. Math. Appl. 77(4): 1029-1041 (2019) - [j8]Bonan Zhao, Xiaoshan Zhang, Zheng Li, Xianliang Hu
A multi-scale strategy for deep semantic segmentation with convolutional neural networks. Neurocomputing 365: 273-284 (2019) - 2018
- [j7]Xianliang Hu, Yixin Li, Hangjie Ji
A nodal finite element approximation of a phase field model for shape and topology optimization. Appl. Math. Comput. 339: 675-684 (2018) - [j6]Xianliang Hu, Danfu Han, Jiang Zhu
Spline element methods allowing multiple level hanging nodes. J. Comput. Appl. Math. 337: 125-134 (2018) - [j5]Shengfeng Zhu
A level set method for shape optimization in semilinear elliptic problems. J. Comput. Phys. 355: 104-120 (2018) - [j4]Shengyang Wu, Xianliang Hu, Shengfeng Zhu
A multi-mesh finite element method for phase-field based photonic band structure optimization. J. Comput. Phys. 357: 324-337 (2018) - 2016
- [j3]Xinping Shao, Danfu Han, Xianliang Hu:
A p-version two level spline method for 2D Navier-Stokes equations. Comput. Math. Appl. 71(12): 2557-2567 (2016) - [j2]Xinping Shao, Danfu Han, Xianliang Hu:
Two-Level Spline Approximations for Two-Dimensional Navier-Stokes Equations. Comput. Methods Appl. Math. 16(3): 497-506 (2016) - 2015
- [c1]Dong Jiang, Xianliang Hu, Danfu Han:
A cubic spline approach for solving the arterial graft design problem. BMEI 2015: 265-269
2000 – 2009
- 2007
- [j1]Xianliang Hu, Danfu Han, Ming-Jun Lai:
Bivariate Splines of Various Degrees for Numerical Solution of Partial Differential Equations. SIAM J. Sci. Comput. 29(3): 1338-1354 (2007)
Coauthor Index
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