Meng Ding

1.3k citations
96 papers · 839 indexed · h-index 17

Impact in

Papers in

Meng Ding

85 papers receiving 811 citations

Peers

Meng Ding
Comparison fields: 5 of 116
  • Computer Vision and Pattern Recognition 394
  • Media Technology 104
  • Aerospace Engineering 285
  • Space and Planetary Science 8
  • Industrial and Manufacturing Engineering 43
Replace Sukhendu Das with:
Sukhendu Das India
Michel Devy France
Yizhou Wang China
Heinz Hertlein United Kingdom
Xinyue Zhao China
Asra Aslam Ireland
Nassim Ammour Saudi Arabia
Cheng Chi China
Meng Ding relative to Sukhendu Das India Sukhendu Das's profile →
Citations per field
00.5×4.8×
Sukhendu Das · 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 96 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201761
2 201842
3 201237
4 202036
5 201232
6 201427
7 201127
8 202226
9 201326
10 201724
11 201524
12 201823
13 201723
14 201623
15 200920
16 202219
17 201818
18 200816
19 202216
20 201015

About Meng Ding

Meng Ding is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering, Media Technology, Business and International Management and Safety, Risk, Reliability and Quality, having authored 96 papers that have together received 839 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (21 papers), Infrared Target Detection Methodologies (17 papers), Robotics and Sensor-Based Localization (17 papers), Advanced Vision and Imaging (13 papers), Image Enhancement Techniques (10 papers), Robotic Path Planning Algorithms (8 papers), Advanced Measurement and Detection Methods (8 papers) and Artificial Intelligence in Games (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (394 citations), Media Technology (104 citations), Aerospace Engineering (285 citations), Space and Planetary Science (8 citations) and Industrial and Manufacturing Engineering (43 citations). Meng Ding has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yunfeng Cao, Bangfeng Wang, Ruofeng Tong, Qingxian Wu, Li Wei, Wei Li, Li Xiao, Wen‐Hua Chen, Ping Zhao and Jin Li. Their work appears in journals such as Applied Sciences, Chinese Journal of Aeronautics, IET Intelligent Transport Systems, Signal Processing Image Communication and IEEE Access.

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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