Sheng Ding

526 total citations
26 papers, 377 citations indexed

About

Sheng Ding is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Sheng Ding has authored 26 papers receiving a total of 377 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Media Technology, 5 papers in Computer Vision and Pattern Recognition and 5 papers in Artificial Intelligence. Recurrent topics in Sheng Ding's work include Remote-Sensing Image Classification (5 papers), Remote Sensing and Land Use (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Sheng Ding is often cited by papers focused on Remote-Sensing Image Classification (5 papers), Remote Sensing and Land Use (4 papers) and Anomaly Detection Techniques and Applications (3 papers). Sheng Ding collaborates with scholars based in China, Canada and Taiwan. Sheng Ding's co-authors include Varun G. Menon, Xiaolong Xu, Mian Ahmad Jan, Gautam Srivastava, Muhammad Bilal, Mohammad R. Khosravi, Maoli Wang, Li Chen, Anne Toppinen and Xiaoyan Wang and has published in prestigious journals such as The Science of The Total Environment, Journal of Hydrology and IEEE Access.

In The Last Decade

Sheng Ding

24 papers receiving 365 citations

Peers

Sheng Ding
Comparison fields: 5 of 91
  • Computer Networks and Communications 158
  • Electrical and Electronic Engineering 89
  • Artificial Intelligence 79
  • Information Systems 52
  • Industrial and Manufacturing Engineering 49
Replace Prateek Chaturvedi with:
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Eustace M. Dogo South Africa
Gang Xiao China
Geng Chen China
Muhammad Nabeel Asghar Pakistan
Tao Ren China
Endah Kristiani Taiwan
T. Saravanan India
Sung‐Jung Hsiao Taiwan
Prateek Chaturvedi India View profile →
Citations per field, relative to Sheng Ding
Sheng Ding · 1×
Citations per year, relative to Sheng Ding
Sheng Ding · 1×

Countries citing papers authored by Sheng Ding

Since Specialization
Citations

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

Fields of papers citing papers by Sheng Ding

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheng Ding

This figure shows the co-authorship network connecting the top 25 collaborators of Sheng Ding. A scholar is included among the top collaborators of Sheng Ding 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 Sheng Ding. Sheng Ding 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 0
2 0
3 1
4 13
5 1
6 17
7 27
8 8
9 184
10 2
11 6
12 1
13 28
14 2
15 3
16 1
17 6
18 14
19 1
20 5

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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