Ding Liu

5.0k total citations
252 papers, 3.5k citations indexed

About

Ding Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Ding Liu has authored 252 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Computer Vision and Pattern Recognition, 62 papers in Artificial Intelligence and 59 papers in Control and Systems Engineering. Recurrent topics in Ding Liu's work include Advanced Algorithms and Applications (20 papers), Image Processing Techniques and Applications (17 papers) and Robotics and Sensor-Based Localization (15 papers). Ding Liu is often cited by papers focused on Advanced Algorithms and Applications (20 papers), Image Processing Techniques and Applications (17 papers) and Robotics and Sensor-Based Localization (15 papers). Ding Liu collaborates with scholars based in China, United States and Canada. Ding Liu's co-authors include Junli Liang, Han Liu, Daniel Gildea, Jing Xin, Youmin Zhang, Bihan Wen, Ying-En Ge, Yingmin Yi, Shuaishuai Lin and Fangqiu Xu and has published in prestigious journals such as PLoS ONE, Journal of Cleaner Production and Scientific Reports.

In The Last Decade

Ding Liu

221 papers receiving 3.3k citations

Peers

Ding Liu
Comparison fields: 5 of 156
  • Computer Vision and Pattern Recognition 995
  • Artificial Intelligence 721
  • Electrical and Electronic Engineering 716
  • Signal Processing 376
  • Control and Systems Engineering 359
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Kunfeng Wang China View profile →
Citations per field, relative to Ding Liu
Ding Liu · 1×
Citations per year, relative to Ding Liu
Ding Liu · 1×

Countries citing papers authored by Ding Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ding Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ding Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ding Liu. A scholar is included among the top collaborators of Ding Liu 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 Ding Liu. Ding Liu 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 4
2 8
3 2
4 8
5 0
6 9
7 60
8 2
9 3
10 12
11 14
12
A Novel Classifier Based on Quantum Computation
7
13
Semantic Role Features for Machine Translation
61
14
Research on translation table heuristic algorithm
5
15 8
16
Assessment of Surface Contamination of High Voltage Insulator Based on Least Squares Support Vector Machine
3
17
SHORT-TERM LOAD FORECASTING BASED ON WAVELET TRANSFORM AND LEAST SQUARE SUPPORT VECTOR MACHINES
11
18
Syntactic Features for Evaluation of Machine Translation
113
19
Approximate range searching in higher dimension.
1
20
Identification and chaotifying control of a class of system without mathematical model
1

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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