Dat Ngo

25 papers receiving 114 citations

Peers

Dat Ngo
Comparison fields: 5 of 57
  • Signal Processing 38
  • Developmental Biology 3
  • Artificial Intelligence 36
  • Computer Vision and Pattern Recognition 20
  • Pulmonary and Respiratory Medicine 26
Replace Marco Piccirilli with:
Marco Piccirilli United States
Jan Ernst United States
Abdelkrim Ouafi Algeria
Sadegh Mohammadi Iran
Ji Zhu China
Mengyue Geng China
Zhifeng Kong United States
Alexandros Lattas United Kingdom
Zuoxin Li China
Dat Ngo relative to Marco Piccirilli United States Marco Piccirilli's profile →
Citations per field
00.5×8.7×
Marco Piccirilli · 1×
Citations per year

Countries citing papers authored by Dat Ngo

Since Specialization
Citations

This map shows the geographic impact of Dat Ngo'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 Dat Ngo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dat Ngo more than expected).

Fields of papers citing papers by Dat Ngo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Dat Ngo. 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 Dat Ngo. The network helps show where Dat Ngo may publish in the future.

Co-authors

The 25 scholars most cited alongside Dat Ngo, 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 Dat Ngo Line = papers co-authored together Dat Ngo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202135
2 202213
3 20197
4 20186
5 20225
6 20225
7 20235
8 20164
9 20224
10 20234
11 20224
12 20234
13 20233
14 20193
15 20223
16 20182
17 20122
18 20222
19 20251
20 20241

About Dat Ngo

Dat Ngo is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine and Radiology, Nuclear Medicine and Imaging, having authored 29 papers that have together received 119 indexed citations. Recurring topics across this work include Music and Audio Processing (13 papers), Speech and Audio Processing (8 papers), Music Technology and Sound Studies (5 papers), Respiratory and Cough-Related Research (4 papers), Radiomics and Machine Learning in Medical Imaging (3 papers), Phonocardiography and Auscultation Techniques (3 papers), Gene expression and cancer classification (2 papers) and Anomaly Detection Techniques and Applications (2 papers). The work is most often cited by research in Signal Processing (38 citations), Developmental Biology (3 citations), Artificial Intelligence (36 citations), Computer Vision and Pattern Recognition (20 citations) and Pulmonary and Respiratory Medicine (26 citations). Dat Ngo has collaborated with scholars based in Vietnam, United Kingdom and Austria. Frequent co-authors include Lam Pham, Thanh Duc Ngo, Anh Gia-Tuan Nguyen, Alexander Schindler, Ian McLoughlin, Khoa Tran, Delaram Jarchi, Anh‐Tu Nguyen, Hoang Duc Nguyen and Tung Le. Their work appears in journals such as Applied Acoustics, IEEE Journal of Biomedical and Health Informatics, Journal of the American College of Cardiology, Processes and International Journal of Computing.

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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