Kaizhu Huang
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Explore the profile of Kaizhu Huang including associated specialties, affiliations and a list of published articles.
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39
Citations
67
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Recent Articles
11.
Gao P, Yang X, Zhang R, Goulermas J, Geng Y, Yan Y, et al.
Neural Netw
. 2023 Mar;
162:1-10.
PMID: 36878166
In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalized image outpainting problems. Different from most present image outpainting methods conducting horizontal extrapolation, our...
12.
Duan S, Cai T, Zhu J, Yang X, Lim E, Huang K, et al.
Anal Chim Acta
. 2023 Feb;
1248:340868.
PMID: 36813452
Smartphone has long been considered as one excellent platform for disease screening and diagnosis, especially when combined with microfluidic paper-based analytical devices (μPADs) that feature low cost, ease of use,...
13.
Ma W, Yang X, Wang Q, Huang K, Huang X
Cells
. 2022 Dec;
11(24).
PMID: 36552872
3D point clouds are gradually becoming more widely used in the medical field, however, they are rarely used for 3D representation of intracranial vessels and aneurysms due to the time-consuming...
14.
Li P, Wang X, Huang K, Huang Y, Li S, Iqbal M
Sensors (Basel)
. 2022 Aug;
22(16).
PMID: 36015856
Recent advances in both lightweight deep learning algorithms and edge computing increasingly enable multiple model inference tasks to be conducted concurrently on resource-constrained edge devices, allowing us to achieve one...
15.
Ieracitano C, Morabito F, Squartini S, Huang K, Li X, Mahmud M
Cognit Comput
. 2022 Aug;
:1-3.
PMID: 35991007
No abstract available.
16.
Guo J, Huang K, Yi X, Zhang R
IEEE Trans Neural Netw Learn Syst
. 2022 Aug;
35(3):3640-3651.
PMID: 35969544
Graph convolutional networks (GCNs) emerge as the most successful learning models for graph-structured data. Despite their success, existing GCNs usually ignore the entangled latent factors typically arising in real-world graphs,...
17.
Yao K, Su Z, Huang K, Yang X, Sun J, Hussain A, et al.
IEEE J Biomed Health Inform
. 2022 Mar;
26(10):4976-4986.
PMID: 35324451
We consider the problem of volumetric (3D) unsupervised domain adaptation (UDA) in cross-modality medical image segmentation, aiming to perform segmentation on the unannotated target domain (e.g. MRI) with the help...
18.
Zhou Y, Huang K, Cheng C, Wang X, Hussain A, Liu X
IEEE Trans Neural Netw Learn Syst
. 2022 Mar;
34(9):6515-6529.
PMID: 35271450
AdaBelief, one of the current best optimizers, demonstrates superior generalization ability over the popular Adam algorithm by viewing the exponential moving average of observed gradients. AdaBelief is theoretically appealing in...
19.
Yao K, Sun J, Huang K, Jing L, Liu H, Huang D, et al.
Int J Bioprint
. 2022 Feb;
8(1):495.
PMID: 35187282
Fibrous scaffolds have been extensively used in three-dimensional (3D) cell culture systems to establish models in cell biology, tissue engineering, and drug screening. It is a common practice to characterize...
20.
Zhang S, Huang K, Zhu J, Liu Y
Neural Netw
. 2021 Apr;
140:282-293.
PMID: 33839600
We propose a new regularization method for deep learning based on the manifold adversarial training (MAT). Unlike previous regularization and adversarial training methods, MAT further considers the local manifold of...