Ding Liu

5.3k citations
266 papers · 4.1k · 1 hit paper · h-index 32

Impact in

Papers in

Ding Liu

245 papers receiving 3.9k citations

Ding Liu's Hit Papers

A Deep Learning Based Forest Fire Detection Approach Using UAV and YOLOv3 2019 · 193 citations
1930+2+4Years since publication50100150

Peers

Ding Liu
Comparison fields: 5 of 134
  • Signal Processing 351
  • Computer Vision and Pattern Recognition 828
  • Safety, Risk, Reliability and Quality 313
  • Industrial and Manufacturing Engineering 219
  • Artificial Intelligence 673
Replace Wei Wang with:
Wei Wang China
Meiqin Liu China
Zhenyu Liu China
olga fink Switzerland
Yongfang Xie China
Erhan Akın Türkiye
Hichem Snoussi France
Esmat Rashedi Iran
Saeı̈d Saryazdi Iran
Dianhui Wang Australia
Ding Liu relative to Wei Wang China Wei Wang's profile →
Citations per field
00.5×1.5×2.1×
Wei Wang · 1×
Citations per year

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-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 266 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009249
2
Non-local recurrent network for image restoration
2018200
3
A Deep Learning Based Forest Fire Detection Approach Using UAV and YOLOv3
Hit paper breakdown →
2019193
4 2018170
5 2018124
6
Syntactic Features for Evaluation of Machine Translation
2005122
7 2018104
8 201794
9 201793
10 201791
11 202282
12 201774
13 201770
14
Semantic Role Features for Machine Translation
201068
15 202067
16 202367
17 201965
18 200963
19 202158
20 202456

About Ding Liu

Ding Liu is a scholar working on Control and Systems Engineering, Computer Vision and Pattern Recognition, Artificial Intelligence, Industrial and Manufacturing Engineering and Statistical and Nonlinear Physics, having authored 266 papers that have together received 4.1k indexed citations. Recurring topics across this work include Fault Detection and Control Systems (19 papers), Advanced Control Systems Optimization (13 papers), Natural Language Processing Techniques (12 papers), Neural Networks and Applications (10 papers), Advanced Vision and Imaging (10 papers), Chaos control and synchronization (9 papers), Image and Object Detection Techniques (9 papers) and Industrial Vision Systems and Defect Detection (8 papers). The work is most often cited by research in Signal Processing (351 citations), Computer Vision and Pattern Recognition (828 citations), Safety, Risk, Reliability and Quality (313 citations), Industrial and Manufacturing Engineering (219 citations) and Artificial Intelligence (673 citations). Ding Liu has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Junli Liang, Han Liu, Daniel Gildea, Jing Lei Xin, Youmin Zhang, Bihan Wen, Thomas S. Huang, Ying-En Ge, Yingmin Yi and Fangqiu Xu. Their work appears in journals such as IEEE Transactions on Semiconductor Manufacturing, IEEE Sensors Journal, IEEE Transactions on Instrumentation and Measurement, Sensors and Energies.

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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