Meng Ding

1.7k citations
28 papers · 472 · h-index 11

Impact in

Papers in

Meng Ding

25 papers receiving 462 citations

Peers

Meng Ding
Comparison fields: 5 of 60
  • Computational Mathematics 136
  • Media Technology 133
  • Computer Vision and Pattern Recognition 309
  • Computational Mechanics 211
  • Signal Processing 35
Replace Jing‐Hua Yang with:
Jing‐Hua Yang China
Longhao Yuan Japan
Shaoguang Huang China
Wenrui Hu China
Minghua Wang China
Guohua Peng China
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Le Han China
Xie Sheng-li China
Wenbo Mei China
Meng Ding relative to Jing‐Hua Yang China Jing‐Hua Yang's profile →
Citations per field
00.5×1.5×
Jing‐Hua Yang · 1×
Citations per year

Countries citing papers authored by Meng Ding

Since Specialization
Citations

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

Fields of papers citing papers by Meng Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 28 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019106
2 201962
3 202054
4 201836
5 201036
6 202230
7 202221
8 202119
9 202018
10 202218
11 202310
12 202010
13 20089
14 20238
15 20237
16 20235
17 20245
18 20214
19 20253
20 20223

About Meng Ding

Meng Ding is a scholar working on Computer Vision and Pattern Recognition, Computational Mechanics, Computational Mathematics, Media Technology and Radiology, Nuclear Medicine and Imaging, having authored 28 papers that have together received 472 indexed citations. Recurring topics across this work include Sparse and Compressive Sensing Techniques (17 papers), Image and Signal Denoising Methods (15 papers), Tensor decomposition and applications (10 papers), Advanced Image Fusion Techniques (7 papers), Remote-Sensing Image Classification (6 papers), Advanced Neuroimaging Techniques and Applications (4 papers), Advanced Image Processing Techniques (4 papers) and Image Enhancement Techniques (3 papers). The work is most often cited by research in Computational Mathematics (136 citations), Media Technology (133 citations), Computer Vision and Pattern Recognition (309 citations), Computational Mechanics (211 citations) and Signal Processing (35 citations). Meng Ding has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Xi-Le Zhao, Ting‐Zhu Huang, Jing‐Hua Yang, Tian-Hui Ma, Ruofeng Tong, Yong Chen, Xiao Fu, Teng-Yu Ji, Jun Wang and Si Wang. Their work appears in journals such as IEEE Geoscience and Remote Sensing Letters, Applied Mathematics and Computation, IEEE Journal of Selected Topics in Signal Processing, The Visual Computer and SIAM Journal on Imaging Sciences.

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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