Jiajun Wen

1.0k citations
53 papers · 673 · h-index 13

Impact in

Papers in

Jiajun Wen

48 papers receiving 662 citations

Peers

Jiajun Wen
Comparison fields: 5 of 72
  • Computational Mathematics 16
  • Computer Vision and Pattern Recognition 470
  • Media Technology 118
  • Signal Processing 76
  • Artificial Intelligence 224
Replace Zhengming Ma with:
Zhengming Ma China
Edward W. Wild United States
Weizhong Yu China
Francis R. Bach United States
Bin Shen China
Huaijiang Sun China
Dacheng Tao Australia
Sung Ju Hwang South Korea
Jiajun Wen relative to Zhengming Ma China Zhengming Ma's profile →
Citations per field
00.5×2.9×
Zhengming Ma · 1×
Citations per year

Countries citing papers authored by Jiajun Wen

Since Specialization
Citations

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

Fields of papers citing papers by Jiajun Wen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Jiajun Wen, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jiajun Wen Line = papers co-authored together Jiajun Wen links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017117
2 201464
3 201854
4 201649
5 202340
6 201839
7 202235
8 202033
9 201429
10 201423
11 201417
12 201415
13 202313
14 201812
15 201210
16 202310
17 201810
18 20239
19 20229
20 20217

About Jiajun Wen

Jiajun Wen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computational Mechanics, Signal Processing and Media Technology, having authored 53 papers that have together received 673 indexed citations. Recurring topics across this work include Face and Expression Recognition (19 papers), Sparse and Compressive Sensing Techniques (11 papers), Video Surveillance and Tracking Methods (11 papers), Machine Learning and ELM (6 papers), Human Pose and Action Recognition (5 papers), Anomaly Detection Techniques and Applications (5 papers), Domain Adaptation and Few-Shot Learning (5 papers) and Remote-Sensing Image Classification (5 papers). The work is most often cited by research in Computational Mathematics (16 citations), Computer Vision and Pattern Recognition (470 citations), Media Technology (118 citations), Signal Processing (76 citations) and Artificial Intelligence (224 citations). Jiajun Wen has collaborated with scholars based in China, Hong Kong and United States. Frequent co-authors include Zhihui Lai, Wai Keung Wong, Zhihui Lai, Jinrong Cui, Yuwu Lu, Yong Xu, Xiaozhao Fang, Linlin Shen, Can Gao and Jie Zhou. Their work appears in journals such as Pattern Recognition, Information Sciences, International Journal of Approximate Reasoning, Neurocomputing and IEEE Transactions on Cybernetics.

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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