Ningning Liu

416 total citations
25 papers, 272 citations indexed

About

Ningning Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems. According to data from OpenAlex, Ningning Liu has authored 25 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 4 papers in Information Systems. Recurrent topics in Ningning Liu's work include Image Retrieval and Classification Techniques (5 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Sparse and Compressive Sensing Techniques (2 papers). Ningning Liu is often cited by papers focused on Image Retrieval and Classification Techniques (5 papers), Advanced Image and Video Retrieval Techniques (3 papers) and Sparse and Compressive Sensing Techniques (2 papers). Ningning Liu collaborates with scholars based in China, France and Italy. Ningning Liu's co-authors include Yuhuan Sun, Xin Jin, Yunhong Wang, Emmanuel Dellandréa, Xiaodong Li, Geng Zhao, Shiming Ge, Chao Zhu, Tao Feng and Charles‐Edmond Bichot and has published in prestigious journals such as PLoS ONE, Journal of Cleaner Production and Expert Systems with Applications.

In The Last Decade

Ningning Liu

22 papers receiving 254 citations

Peers

Ningning Liu
Comparison fields: 5 of 71
  • Marketing 113
  • Management, Monitoring, Policy and Law 77
  • Computer Vision and Pattern Recognition 62
  • Artificial Intelligence 55
  • Sociology and Political Science 40
Replace Sanjay Singla with:
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Sanjay Singla India View profile →
Citations per field, relative to Ningning Liu
Ningning Liu · 1×
Citations per year, relative to Ningning Liu
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Countries citing papers authored by Ningning Liu

Since Specialization
Citations

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

Fields of papers citing papers by Ningning Liu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ningning Liu

This figure shows the co-authorship network connecting the top 25 collaborators of Ningning Liu. A scholar is included among the top collaborators of Ningning 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 Ningning Liu. Ningning 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 1
2 0
3 0
4 5
5 2
6 0
7 9
8
AI600 Lab at ImageCLEF 2019 Concept Detection Task.
2
9 5
10 11
11 1
12 140
13 8
14 3
15
BUAA-iCC at ImageCLEF 2015 Scalable Concept Image Annotation Challenge
1
16 1
17 26
18 1
19 11
20 3

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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