Mingyi Wang

679 citations
57 papers · 489 · h-index 11

Impact in

Papers in

Mingyi Wang

50 papers receiving 479 citations

Peers

Mingyi Wang
Comparison fields: 5 of 99
  • Media Technology 29
  • Control and Systems Engineering 73
  • Plant Science 111
  • Biophysics 15
  • Computer Vision and Pattern Recognition 50
Replace T. Vijayakumar with:
T. Vijayakumar India
Jayant Kulkarni India
Jiantao Wang China
Manas Ranjan Prusty India
Amal H. Alharbi Saudi Arabia
Deepak Pathak South Korea
Rakesh Chandra Joshi India
W. K. Wong Malaysia
Zaw Zaw Htike Malaysia
Mighty Abra Ayidzoe Ghana
Mingyi Wang relative to T. Vijayakumar India T. Vijayakumar's profile →
Citations per field
00.5×4.5×
T. Vijayakumar · 1×
Citations per year

Countries citing papers authored by Mingyi Wang

Since Specialization
Citations

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

Fields of papers citing papers by Mingyi Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201590
2 201380
3 201346
4 200729
5 200924
6 201619
7 202219
8 202216
9 202315
10 202212
11 201711
12 20108
13 20187
14 20177
15 20197
16 20236
17 20246
18 20206
19 20116
20 20235

About Mingyi Wang

Mingyi Wang is a scholar working on Biomedical Engineering, Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition, Molecular Biology and Media Technology, having authored 57 papers that have together received 489 indexed citations. Recurring topics across this work include Photoacoustic and Ultrasonic Imaging (13 papers), Optical Coherence Tomography Applications (11 papers), Optical Imaging and Spectroscopy Techniques (9 papers), Gene expression and cancer classification (8 papers), Advanced Image Fusion Techniques (7 papers), Bioinformatics and Genomic Networks (7 papers), Remote-Sensing Image Classification (4 papers) and Retinal Imaging and Analysis (4 papers). The work is most often cited by research in Media Technology (29 citations), Control and Systems Engineering (73 citations), Plant Science (111 citations), Biophysics (15 citations) and Computer Vision and Pattern Recognition (50 citations). Mingyi Wang has collaborated with scholars based in China, United States and Macao. Frequent co-authors include Liyi Li, Donghua Pan, Michael K. Udvardi, Jiangqi Wen, Xiaofei Cheng, Zuozhou Chen, Million Tadege, Hee‐Kyung Lee, Sylvie Cloutier and Pascal Ratet. Their work appears in journals such as Journal of Biophotonics, Optics Letters, Journal of Biomedical Optics, IEEE Sensors Journal and Applied Physics Letters.

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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