Liyan Ma

846 citations
76 papers · 606 · h-index 12

Impact in

Papers in

Liyan Ma

67 papers receiving 591 citations

Peers

Liyan Ma
Comparison fields: 5 of 59
  • Computer Vision and Pattern Recognition 271
  • Computational Mathematics 1
  • Health Informatics 3
  • Obstetrics and Gynecology 13
  • Environmental Chemistry 10
Replace Wentao Liu with:
Wentao Liu China
Yueru Chen China
Liman Liu China
Francisco Javier Gallegos-Funes Mexico
Yongchao Wang China
P. S. Eliahim Jeevaraj India
Intaek Kim South Korea
Tung M. Luu South Korea
Thang Vu South Korea
Liyan Ma relative to Wentao Liu China Wentao Liu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Liyan Ma

Since Specialization
Citations

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

Fields of papers citing papers by Liyan Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 76 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201390
2 201656
3 202443
4 201340
5 202329
6 201323
7 202123
8 201518
9 201617
10 202217
11 202414
12 202212
13 202212
14 201711
15 201911
16 202210
17 202310
18 20249
19 20178
20 20218

About Liyan Ma

Liyan Ma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Infectious Diseases, Pharmacology and Plant Science, having authored 76 papers that have together received 606 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Image and Signal Denoising Methods (8 papers), Domain Adaptation and Few-Shot Learning (6 papers), Advanced Vision and Imaging (4 papers), Medical Image Segmentation Techniques (3 papers), Image Enhancement Techniques (3 papers), Clostridium difficile and Clostridium perfringens research (2 papers) and Mycotoxins in Agriculture and Food (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (271 citations), Computational Mathematics (1 citation), Health Informatics (3 citations), Obstetrics and Gynecology (13 citations) and Environmental Chemistry (10 citations). Liyan Ma has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Tieyong Zeng, Lionel Moisan, Xiangfeng Luo, Jian Qiao Yu, Hang Yu, Shaorong Xie, Yan Sun, Michael K. Ng, Liang Zeng and Han Zhang. Their work appears in journals such as Knowledge-Based Systems, IEEE Journal of Biomedical and Health Informatics, Engineering Applications of Artificial Intelligence, PLoS ONE and IEEE Signal Processing 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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