Jingyu Yang

1.9k total citations
29 papers, 1.2k citations indexed

About

Jingyu Yang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Jingyu Yang has authored 29 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 7 papers in Computational Theory and Mathematics. Recurrent topics in Jingyu Yang's work include Video Surveillance and Tracking Methods (9 papers), Rough Sets and Fuzzy Logic (6 papers) and Face and Expression Recognition (5 papers). Jingyu Yang is often cited by papers focused on Video Surveillance and Tracking Methods (9 papers), Rough Sets and Fuzzy Logic (6 papers) and Face and Expression Recognition (5 papers). Jingyu Yang collaborates with scholars based in China, Hong Kong and United States. Jingyu Yang's co-authors include Jian Yang, David Zhang, Ben Niu, Xibei Yang, Dong‐Jun Yu, Jun Hu, Hong‐Bin Shen, Jinhui Tang, Jing Yang and Yuhua Qian and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and Pattern Recognition.

In The Last Decade

Jingyu Yang

26 papers receiving 1.2k citations

Peers

Jingyu Yang
Comparison fields: 5 of 91
  • Computer Vision and Pattern Recognition 665
  • Computational Theory and Mathematics 341
  • Artificial Intelligence 266
  • Information Systems 179
  • Signal Processing 172
Replace Xiaolong Teng with:
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Patrick M. Murphy United States
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Xiaolong Teng China View profile →
Citations per field, relative to Jingyu Yang
Jingyu Yang · 1×
Citations per year, relative to Jingyu Yang
Jingyu Yang · 1×

Countries citing papers authored by Jingyu Yang

Since Specialization
Citations

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

Fields of papers citing papers by Jingyu Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jingyu Yang

This figure shows the co-authorship network connecting the top 25 collaborators of Jingyu Yang. A scholar is included among the top collaborators of Jingyu Yang 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 Jingyu Yang. Jingyu Yang 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 0
3 98
4 65
5 6
6 114
7 56
8 54
9 23
10 2
11 1
12 1
13
Energy Efficient Reliable Multi-path Routing Using Network Coding for Sensor Network
12
14 4
15
Kernel nearest neighbor convex hull classifier with kernel subspace sample selection method
0
16 359
17 21
18 17
19 70
20 1

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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