Limin Liu

413 total citations
33 papers, 156 citations indexed

About

Limin Liu is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Limin Liu has authored 33 papers receiving a total of 156 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 9 papers in Signal Processing and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Limin Liu's work include Radar Systems and Signal Processing (5 papers), Wireless Signal Modulation Classification (4 papers) and Remote Sensing and LiDAR Applications (3 papers). Limin Liu is often cited by papers focused on Radar Systems and Signal Processing (5 papers), Wireless Signal Modulation Classification (4 papers) and Remote Sensing and LiDAR Applications (3 papers). Limin Liu collaborates with scholars based in China, United States and Singapore. Limin Liu's co-authors include Michael Halper, James Geller, Yehoshua Perl, Jiwu Jing, Daren Zha, Debin Gao, Jian Dong, Jin Han, Ping Lang and Xiongjun Fu and has published in prestigious journals such as Information Sciences, IEEE Transactions on Knowledge and Data Engineering and Agronomy.

In The Last Decade

Limin Liu

29 papers receiving 149 citations

Peers

Limin Liu
Comparison fields: 5 of 55
  • Artificial Intelligence 83
  • Signal Processing 41
  • Information Systems 36
  • Computer Networks and Communications 31
  • Molecular Biology 27
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Johannes Singler Germany
Vadim Sheinin United States
Patrick K. Nicholson United States
Ahmed Salem China
Benjamin Sach United Kingdom
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Pierre Genevès France
Luca Demetrio Italy
Vassilis N. Ioannidis United States
Ahoud Alhazmi Australia View profile →
Citations per field, relative to Limin Liu
Limin Liu · 1×
Citations per year, relative to Limin Liu
Limin Liu · 1×

Countries citing papers authored by Limin Liu

Since Specialization
Citations

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

Fields of papers citing papers by Limin Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Limin Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Limin Liu. A scholar is included among the top collaborators of Limin 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 Limin Liu. Limin 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 0
2 1
3 4
4 1
5 1
6 1
7 4
8 9
9 1
10 9
11 0
12 1
13 2
14 2
15 2
16
Consistent testing for lag length in cointegrated relationships
4
17 2
18 3
19 9
20 12

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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