Xiaojun Chen
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 1%
- Information Systems top 2%
- Computer Networks and Communications top 5%
- Electrical and Electronic Engineering
- Co-authors
- Joshua Zhexue HuangMin YangFeiping NieYunming YeZhou ZhaoSalman SalloumXiaofei XuRuslan Dautov
- Topics
- Face and Expression Recognition (23 papers)Topic Modeling (20 papers)Text and Document Classification Technologies (14 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Xiaojun Chen
118 papers receiving 2.7k citations
Hit Papers
Peers
Comparison fields: 5 of 151
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 948
- Information Systems 393
- Computer Networks and Communications 255
- Electrical and Electronic Engineering 235
Countries citing papers authored by Xiaojun Chen
This map shows the geographic impact of Xiaojun Chen'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 Xiaojun Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Xiaojun Chen more than expected).
Fields of papers citing papers by Xiaojun Chen
This network shows the impact of papers produced by Xiaojun Chen. 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 Xiaojun Chen. The network helps show where Xiaojun Chen may publish in the future.
Co-authorship network of co-authors of Xiaojun Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojun Chen. A scholar is included among the top collaborators of Xiaojun Chen 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 Xiaojun Chen. Xiaojun Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 8 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 1 | |
| 6 | 14 | |
| 7 | 4 | |
| 8 | 1 | |
| 9 | 14 | |
| 10 | 9 | |
| 11 | 42 | |
| 12 | 36 | |
| 13 | 49 | |
| 14 | 45 | |
| 15 | 2 | |
| 16 | 16 | |
| 17 | 101 | |
| 18 | Big data analytics on Apache Sparkbreakdown → | 261 |
| 19 | 2 | |
| 20 | A comprehensive review of the theories and practices of emergency management capability assessment | 4 |
About Xiaojun Chen
Xiaojun Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Information Systems, having authored 122 papers that have together received 2.9k indexed citations. Recurring topics across this work include Face and Expression Recognition (23 papers), Topic Modeling (20 papers) and Text and Document Classification Technologies (14 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (948 citations), Artificial Intelligence (1.3k citations) and Urban Studies (122 citations). Xiaojun Chen has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Joshua Zhexue Huang, Min Yang, Feiping Nie, Yunming Ye, Zhou Zhao, Salman Salloum, Xiaofei Xu, Ruslan Dautov, Qingyao Wu and Wenting Tu. Their work appears in journals such as Nature Communications, Nano Letters and Journal of Applied Physics.
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.