Lingzhi Liu

1.0k citations
56 papers · 780 indexed · h-index 17
Topics
Video Coding and Compression Technologies (7 papers)Advanced Neural Network Applications (7 papers)Advanced Vision and Imaging (7 papers)
Partner nations
ChinaUnited StatesJapan

In The Last Decade

Lingzhi Liu

54 papers receiving 755 citations

Peers

Lingzhi Liu
Comparison fields: 5 of 105
  • Computer Vision and Pattern Recognition 213
  • Electrical and Electronic Engineering 172
  • Plant Science 148
  • Signal Processing 120
  • Pollution 99
Replace Binqiang Wang with:
Binqiang Wang China
Yuqing Liu China
Shamsa Kanwal Pakistan
Fangling Jiang China
Zhensong Zhang China
Jinyang Li China
Vineet Srivastava India
Deguang Li China
Md. Rashedul Islam Bangladesh
Shan Zhou China
Lingzhi Liu relative to Binqiang Wang China Binqiang Wang's profile →
Citations per field
00.5×4.3×
Binqiang Wang · 1×
Citations per year

Countries citing papers authored by Lingzhi Liu

Since Specialization
Citations

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

Fields of papers citing papers by Lingzhi Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lingzhi Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Lingzhi Liu. A scholar is included among the top collaborators of Lingzhi 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 Lingzhi Liu. Lingzhi 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 16
2 5
3 1
4 12
5 2
6 15
7 1
8 22
9 1
10 55
11 19
12 7
13 30
14
Study on Li-ion Battery Management System
1
15 3
16
A Realizing Scheme of Mine Through-the-earth Communication System with Digitization
0
17 3
18 27
19 4
20 2

About Lingzhi Liu

Lingzhi Liu is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Soil Science, having authored 56 papers that have together received 780 indexed citations. Recurring topics across this work include Video Coding and Compression Technologies (7 papers), Advanced Neural Network Applications (7 papers) and Advanced Vision and Imaging (7 papers). The work is most often cited by research in Signal Processing (120 citations), Computer Vision and Pattern Recognition (213 citations) and Pollution (99 citations). Lingzhi Liu has collaborated with scholars based in China, United States and Japan. Frequent co-authors include Zongqiang Gong, Yulong Zhang, Shi Chen, Peijun Li, Ke Xu, Dong Wang, Peijun Li, Rong Meng-tian, Sijun Qin and Deguo Lyu. Their work appears in journals such as PLoS ONE, Analytical Chemistry and IEEE Transactions on Image Processing.

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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