Jun Xing
- Computer Vision and Pattern Recognition top 5%
- Computational Mechanics top 5%
- Computer Graphics and Computer-Aided Design top 2%
- Information Systems top 5%
- Computer Networks and Communications top 10%
- Topics
- Advanced Electrical Measurement Techniques (7 papers)Computer Graphics and Visualization Techniques (6 papers)Face recognition and analysis (6 papers)
- Cited by
- Computer Graphics and Computer-Aided DesignComputer Vision and Pattern RecognitionHuman-Computer Interaction
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
Jun Xing
40 papers receiving 658 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 352
- Computational Mechanics 164
- Computer Graphics and Computer-Aided Design 115
- Information Systems 110
- Computer Networks and Communications 95
Countries citing papers authored by Jun Xing
This map shows the geographic impact of Jun Xing'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 Jun Xing with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Xing more than expected).
Fields of papers citing papers by Jun Xing
This network shows the impact of papers produced by Jun Xing. 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 Jun Xing. The network helps show where Jun Xing may publish in the future.
Co-authorship network of co-authors of Jun Xing
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Xing. A scholar is included among the top collaborators of Jun Xing 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 Jun Xing. Jun Xing is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 1 | |
| 6 | 1 | |
| 7 | SG-PBFT: A secure and highly efficient distributed blockchain PBFT consensus algorithm for intelligent Internet of vehiclesbreakdown → | 138 |
| 8 | 19 | |
| 9 | 18 | |
| 10 | 15 | |
| 11 | Single-View Hair Reconstruction using Convolutional Neural Networks | 2 |
| 12 | 1 | |
| 13 | 40 | |
| 14 | 1 | |
| 15 | 95 | |
| 16 | 37 | |
| 17 | A Global Intelligent Optimization Algorithm Based on Membrane Systems | 0 |
| 18 | Pregnancy Outcome in Aged Pregnant Women | 1 |
| 19 | An Ontology Learning Method Based on Double VSM and Fuzzy FCA | 2 |
| 20 | Edge Detection of Sobel-Based Digital Image | 4 |
About Jun Xing
Jun Xing is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Computational Mechanics, having authored 44 papers that have together received 682 indexed citations. Recurring topics across this work include Advanced Electrical Measurement Techniques (7 papers), Computer Graphics and Visualization Techniques (6 papers) and Face recognition and analysis (6 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (115 citations), Computer Vision and Pattern Recognition (352 citations) and Human-Computer Interaction (49 citations). Jun Xing has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Li‐Yi Wei, Hao Li, Koki Nagano, Tao Luo, Naixue Xiong, Xiaochun Cheng, Xi Zheng, Guangquan Xu, Shaoying Liu and Shunsuke Saito. Their work appears in journals such as The Science of The Total Environment, Chemosphere and IEEE Access.
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.