Michael K Ng
Overview
Explore the profile of Michael K Ng including associated specialties, affiliations and a list of published articles.
Author names and details appear as published. Due to indexing inconsistencies, multiple individuals may share a name, and a single author may have variations. MedLuna displays this data as publicly available, without modification or verification
Snapshot
Snapshot
Articles
83
Citations
372
Followers
0
Related Specialties
Related Specialties
Top 10 Co-Authors
Top 10 Co-Authors
Published In
Published In
Affiliations
Affiliations
Soon will be listed here.
Recent Articles
11.
Yu W, Lei B, Wang S, Liu Y, Feng Z, Hu Y, et al.
IEEE Trans Neural Netw Learn Syst
. 2022 Mar;
34(8):4401-4415.
PMID: 35320106
The diagnosis of early stages of Alzheimer's disease (AD) is essential for timely treatment to slow further deterioration. Visualizing the morphological features for early stages of AD is of great...
12.
Zhao X, Yang J, Ma T, Jiang T, Ng M, Huang T
IEEE Trans Image Process
. 2021 Dec;
31:984-999.
PMID: 34971534
Completing missing entries in multidimensional visual data is a typical ill-posed problem that requires appropriate exploitation of prior information of the underlying data. Commonly used priors can be roughly categorized...
13.
Abetz J, Mangira D, Ng M
ANZ J Surg
. 2021 Oct;
92(4):904-905.
PMID: 34605592
No abstract available.
14.
Zhuang L, Ng M
IEEE Trans Neural Netw Learn Syst
. 2021 Sep;
34(8):4702-4716.
PMID: 34587098
The decrease in the widths of spectral bands in hyperspectral imaging leads to a decrease in signal-to-noise ratio (SNR) of measurements. The decreased SNR reduces the reliability of measured features...
15.
Zhang H, Zhao X, Jiang T, Ng M, Huang T
IEEE Trans Cybern
. 2021 Sep;
52(12):13395-13410.
PMID: 34543216
The general tensor-based methods can recover missing values of multidimensional images by exploiting the low-rankness on the pixel level. However, especially when considerable pixels of an image are missing, the...
16.
Jiang T, Zhao X, Zhang H, Ng M
IEEE Trans Neural Netw Learn Syst
. 2021 Aug;
34(2):932-946.
PMID: 34464263
In this article, we propose a novel tensor learning and coding model for third-order data completion. The aim of our model is to learn a data-adaptive dictionary from given observations...
17.
Wu H, Zhu H, Yan Y, Wu J, Zhang Y, Ng M
IEEE Trans Image Process
. 2021 Jul;
30:6364-6376.
PMID: 34236965
Heterogeneous domain adaptation (HDA) is a challenging problem because of the different feature representations in the source and target domains. Most HDA methods search for mapping matrices from the source...
18.
Yu W, Lei B, Ng M, Cheung A, Shen Y, Wang S
IEEE Trans Neural Netw Learn Syst
. 2021 Mar;
33(9):4945-4959.
PMID: 33729958
It is of great significance to apply deep learning for the early diagnosis of Alzheimer's disease (AD). In this work, a novel tensorizing GAN with high-order pooling is proposed to...
19.
Wang J, Huang T, Zhao X, Jiang T, Ng M
IEEE Trans Image Process
. 2021 Mar;
30:3581-3596.
PMID: 33684037
This paper addresses the tensor completion problem, which aims to recover missing information of multi-dimensional images. How to represent a low-rank structure embedded in the underlying data is the key...
20.
Zhang X, Ng M
IEEE Trans Pattern Anal Mach Intell
. 2021 Feb;
44(8):4239-4251.
PMID: 33587697
Poisson observations for videos are important models in video processing and computer vision. In this paper, we study the third-order tensor completion problem with Poisson observations. The main aim is...