Liyong Ma

595 total citations
50 papers, 415 citations indexed

About

Liyong Ma is a scholar working on Computer Vision and Pattern Recognition, Biomedical Engineering and Media Technology. According to data from OpenAlex, Liyong Ma has authored 50 papers receiving a total of 415 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Computer Vision and Pattern Recognition, 12 papers in Biomedical Engineering and 11 papers in Media Technology. Recurrent topics in Liyong Ma's work include Advanced Image Fusion Techniques (9 papers), Photoacoustic and Ultrasonic Imaging (9 papers) and Image and Signal Denoising Methods (8 papers). Liyong Ma is often cited by papers focused on Advanced Image Fusion Techniques (9 papers), Photoacoustic and Ultrasonic Imaging (9 papers) and Image and Signal Denoising Methods (8 papers). Liyong Ma collaborates with scholars based in China. Liyong Ma's co-authors include Yong Zhang, Xuguang Wang, Yuejun Liu, Naizhang Feng, Yi Shen, Mingjian Sun, Xuewei Liu, Shuli Jia, Hongjie Wang and Jiachen Ma and has published in prestigious journals such as Optics Express, Applied Sciences and Nuclear Instruments and Methods in Physics Research Section A Accelerators Spectrometers Detectors and Associated Equipment.

In The Last Decade

Liyong Ma

43 papers receiving 387 citations

Peers

Liyong Ma
Comparison fields: 5 of 96
  • Radiology, Nuclear Medicine and Imaging 103
  • Biomedical Engineering 100
  • Computer Vision and Pattern Recognition 88
  • Artificial Intelligence 83
  • Mechanics of Materials 59
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Maciej Kusy Poland
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Pengyu Wang China View profile →
Citations per field, relative to Liyong Ma
Liyong Ma · 1×
Citations per year, relative to Liyong Ma
Liyong Ma · 1×

Countries citing papers authored by Liyong Ma

Since Specialization
Citations

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

Fields of papers citing papers by Liyong Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Liyong Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Liyong Ma. A scholar is included among the top collaborators of Liyong Ma based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liyong Ma. Liyong Ma is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
# Work Indexed citations
1 1
2 0
3 1
4 1
5 4
6 11
7
Extreme Learning Machine Based Defect Detection for Solder Joints
4
8 19
9 25
10
Support Tucker machines based marine oil spill detection using SAR images
8
11 6
12 2
13 12
14 1
15 20
16 18
17 3
18
Pixel Fusion Based Curvelets and Wavelets Denoise Algorithm
5
19 6
20 2

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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