Quan Liu

97 papers receiving 1.2k citations

Hit Papers

Electrocardiogram generation with a bidirectional LSTM-CN...20192026202120232019100200300400

Peers

Quan Liu
Comparison fields: 5 of 168
  • Artificial Intelligence 505
  • Biomedical Engineering 130
  • Cardiology and Cardiovascular Medicine 129
  • Computer Vision and Pattern Recognition 128
  • Electrical and Electronic Engineering 116
Replace Ajay Shrestha with:
Ajay Shrestha United States
Xingbo Wang China
Jiawei Li China
Ali Mansour France
Yuhan Dong China
Fei Ye China
Donglai Wei United States
Liping Li China
Sejong Oh South Korea
R. Kumar India
Quan Liu relative to Ajay Shrestha United States Ajay Shrestha's profile →
Citations per field
00.5×3.3×
Ajay Shrestha · 1×
Citations per year

Countries citing papers authored by Quan Liu

Since Specialization
Citations

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

Fields of papers citing papers by Quan Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Quan Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Quan Liu. A scholar is included among the top collaborators of Quan 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 Quan Liu. Quan 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
#WorkIndexed citations
1 0
2 2
3 12
4 5
5 3
6 1
7 1
8 6
9 16
10 1
11 2
12 90
13 7
14 27
15
The ZHI-EDL System for Entity Discovery and Linking at TAC KBP 2017.
0
16 9
17 4
18
An Algorithm for Hole Recovery in Wireless Sensor Networks Based on Triangle Net
1
19
Foreground object detection based on time information window adaptive kernel density estimation
1
20
Research on algorithm of reinforcement learning
0

About Quan Liu

Quan Liu is a scholar working on Artificial Intelligence, Computational Theory and Mathematics and Information Systems, having authored 111 papers that have together received 1.2k indexed citations. Recurring topics across this work include Reinforcement Learning in Robotics (28 papers), Topic Modeling (22 papers) and Natural Language Processing Techniques (15 papers). The work is most often cited by research in Artificial Intelligence (505 citations), Health Informatics (21 citations) and Acoustics and Ultrasonics (10 citations). Quan Liu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Fei Zhu, Bairong Shen, Fei Ye, Zhen-Hua Ling, Xiaodan Zhu, Jia-Chen Gu, Si Wei, Yuchen Fu, Tianda Li and Yuankai Huo. Their work appears in journals such as Remote Sensing of Environment, Chemical Communications and Scientific Reports.

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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