Michael K Ng
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Explore the profile of Michael K Ng including associated specialties, affiliations and a list of published articles.
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83
Citations
372
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Recent Articles
1.
Jia Z, Xiang Y, Zhao M, Wu T, Ng M
IEEE Trans Image Process
. 2025 Mar;
PP.
PMID: 40031309
The cross-channel deblurring problem in color image processing is difficult to solve due to the complex coupling and structural blurring of color pixels. Until now, there are few efficient algorithms...
2.
Cui L, Guo G, Ng M, Zou Q, Qiu Y
Brief Bioinform
. 2024 Dec;
26(1).
PMID: 39680741
Single-cell multi-omics refers to the various types of biological data at the single-cell level. These data have enabled insight and resolution to cellular phenotypes, biological processes, and developmental stages. Current...
3.
Luo Y, Zhao X, Li Z, Ng M, Meng D
IEEE Trans Pattern Anal Mach Intell
. 2023 Dec;
46(5):3351-3369.
PMID: 38090828
Since higher-order tensors are naturally suitable for representing multi-dimensional data in real-world, e.g., color images and videos, low-rank tensor representation has become one of the emerging areas in machine learning...
4.
Wu H, Yip A, Long J, Zhang J, Ng M
IEEE Trans Pattern Anal Mach Intell
. 2023 Oct;
46(1):561-575.
PMID: 37831564
Graph-structured data, where nodes exhibit either pair-wise or high-order relations, are ubiquitous and essential in graph learning. Despite the great achievement made by existing graph learning models, these models use...
5.
Yeung T, Cheung K, Ng M, See S, Yip A
Neural Comput
. 2023 Jul;
35(10):1678-1712.
PMID: 37523461
The task of transfer learning using pretrained convolutional neural networks is considered. We propose a convolution-SVD layer to analyze the convolution operators with a singular value decomposition computed in the...
6.
Zhuang L, Ng M, Gao L, Michalski J, Wang Z
IEEE Trans Neural Netw Learn Syst
. 2023 Jul;
35(11):16262-16276.
PMID: 37467089
The performance of deep learning-based denoisers highly depends on the quantity and quality of training data. However, paired noisy-clean training images are generally unavailable in hyperspectral remote sensing areas. To...
7.
Li X, Ng M, Xu G, Yip A
Neural Netw
. 2023 Feb;
161:343-358.
PMID: 36774871
The class of multi-relational graph convolutional networks (MRGCNs) is a recent extension of standard graph convolutional networks (GCNs) to handle heterogenous graphs with multiple types of relationships. MRGCNs have been...
8.
Liu Y, Pan J, Ng M
Neural Netw
. 2023 Jan;
160:63-83.
PMID: 36621171
Deep neural networks have achieved great success in solving many machine learning and computer vision problems. In this paper, we propose a deep neural network called the Tucker network derived...
9.
Jia Z, Jin Q, Ng M, Zhao X
IEEE Trans Image Process
. 2022 May;
31:3868-3883.
PMID: 35617180
The image nonlocal self-similarity (NSS) prior refers to the fact that a local patch often has many nonlocal similar patches to it across the image and has been widely applied...
10.
Luo Y, Zhao X, Jiang T, Chang Y, Ng M, Li C
IEEE Trans Image Process
. 2022 May;
31:3793-3808.
PMID: 35609097
Recently, transform-based tensor nuclear norm (TNN) minimization methods have received increasing attention for recovering third-order tensors in multi-dimensional imaging problems. The main idea of these methods is to perform the...