D.B.H. Tay

2.0k citations
124 papers · 1.4k indexed · h-index 19

Impact in

Papers in

D.B.H. Tay

120 papers receiving 1.4k citations

Peers

D.B.H. Tay
Comparison fields: 5 of 104
  • Signal Processing 527
  • Computer Vision and Pattern Recognition 727
  • Media Technology 125
  • Cardiology and Cardiovascular Medicine 292
  • Applied Mathematics 109
Replace Abou‐Bakr M. Youssef with:
Abou‐Bakr M. Youssef Egypt
Vladimír Britaňák Slovakia
Zahir M. Hussain Australia
Libo Zhang China
Irena Orović Montenegro
Mhamed Sayyouri Morocco
Tohru Nitta Japan
T. Thong United States
Shiv Dutt Joshi India
Hicham Karmouni Morocco
D.B.H. Tay relative to Abou‐Bakr M. Youssef Egypt Abou‐Bakr M. Youssef's profile →
Citations per field
00.5×5.3×
Abou‐Bakr M. Youssef · 1×
Citations per year

Countries citing papers authored by D.B.H. Tay

Since Specialization
Citations

This map shows the geographic impact of D.B.H. Tay's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by D.B.H. Tay with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites D.B.H. Tay more than expected).

Fields of papers citing papers by D.B.H. Tay

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D.B.H. Tay. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by D.B.H. Tay. The network helps show where D.B.H. Tay may publish in the future.

Co-authorship network

The 25 scholars most cited alongside D.B.H. Tay, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with D.B.H. Tay Line = papers co-authored together D.B.H. Tay links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20234
3 20230
4 202018
5 202016
6 20195
7 20189
8 20163
9 20164
10 201546
11 20153
12 201215
13 200544
14
Use of arterial transfer functions for the derivation of central aortic waveform characteristics in subjects with type 2 diabetes and cardiovascular disease [6] (multiple letter)
20041
15 20042
16 20030
17 20022
18 20022
19 20014
20 1993120

About D.B.H. Tay

D.B.H. Tay is a scholar working on Signal Processing, Computer Vision and Pattern Recognition, Computational Mathematics, Applied Mathematics and Statistical and Nonlinear Physics, having authored 124 papers that have together received 1.4k indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (74 papers), Digital Filter Design and Implementation (59 papers), Advanced Data Compression Techniques (25 papers), Advanced Graph Neural Networks (24 papers), Complex Network Analysis Techniques (13 papers), Advanced Numerical Analysis Techniques (12 papers), Mathematical Analysis and Transform Methods (10 papers) and Structural Health Monitoring Techniques (9 papers). The work is most often cited by research in Signal Processing (527 citations), Computer Vision and Pattern Recognition (727 citations), Media Technology (125 citations), Cardiology and Cardiovascular Medicine (292 citations) and Applied Mathematics (109 citations). D.B.H. Tay has collaborated with scholars based in Australia, Singapore and China. Frequent co-authors include N. Kingsbury, James D. Cameron, Sarah A. Hope, Ian T. Meredith, Zhiping Lin, Marimuthu Palaniswami, Guang Deng, Junzheng Jiang, Slaven Marusic and Jingxin Zhang. Their work appears in journals such as IEEE Signal Processing Letters, Signal Processing, IEEE Transactions on Signal Processing, Journal of Hypertension and IEEE Transactions on Image Processing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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