Ying Liu

3.4k total citations
156 papers, 2.5k citations indexed

About

Ying Liu is a scholar working on Artificial Intelligence, Signal Processing and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ying Liu has authored 156 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 68 papers in Artificial Intelligence, 32 papers in Signal Processing and 30 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ying Liu's work include Advanced Adaptive Filtering Techniques (19 papers), Blind Source Separation Techniques (18 papers) and Anomaly Detection Techniques and Applications (10 papers). Ying Liu is often cited by papers focused on Advanced Adaptive Filtering Techniques (19 papers), Blind Source Separation Techniques (18 papers) and Anomaly Detection Techniques and Applications (10 papers). Ying Liu collaborates with scholars based in China, United States and United Kingdom. Ying Liu's co-authors include Chunguang Li, Zhaoyang Zhang, Xiaoan Yan, Minping Jia, K.S. Tang, Tao Zhou, Younghae Do, Ming Tang, Zhaoting Liu and Jun Zhao and has published in prestigious journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

Ying Liu

148 papers receiving 2.4k citations

Peers

Ying Liu
Comparison fields: 5 of 157
  • Artificial Intelligence 795
  • Computer Networks and Communications 529
  • Computational Mechanics 442
  • Signal Processing 364
  • Control and Systems Engineering 298
Replace Nikos E. Mastorakis with:
Nikos E. Mastorakis Bulgaria
Qianli Ma China
Nurhan Karaboğa Türkiye
Mehrdad Mahdavi United States
Jagdish C. Patra Singapore
Marius Kloft Germany
Muhammad Sulaiman Pakistan
M. N. S. Swamy Canada
Simone Scardapane Italy
Xiangmin Zhou Australia
Nikos E. Mastorakis Bulgaria View profile →
Citations per field, relative to Ying Liu
Ying Liu · 1×
Citations per year, relative to Ying Liu
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Countries citing papers authored by Ying Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ying Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Liu. A scholar is included among the top collaborators of Ying 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 Ying Liu. Ying 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 2
2 3
3 4
4 1
5 1
6 16
7 1
8 24
9 1
10 0
11 42
12 4
13 9
14 3
15 10
16 26
17 2
18 23
19 57
20 15

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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