Jun Peng
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Control and Systems Engineering top 5%
- Mechanical Engineering top 10%
- Computer Networks and Communications top 10%
- Topics
- Chaos-based Image/Signal Encryption (23 papers)Neural Networks and Applications (12 papers)Chaos control and synchronization (12 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceControl and Systems Engineering
- Journals
- Journal of Cleaner ProductionScientific ReportsIEEE Journal on Selected Areas in Communications
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Peng
146 papers receiving 978 citations
Peers
Comparison fields: 5 of 113
- Artificial Intelligence 271
- Computer Vision and Pattern Recognition 255
- Control and Systems Engineering 192
- Mechanical Engineering 178
- Computer Networks and Communications 122
Countries citing papers authored by Jun Peng
This map shows the geographic impact of Jun Peng'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 Peng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Peng more than expected).
Fields of papers citing papers by Jun Peng
This network shows the impact of papers produced by Jun Peng. 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 Peng. The network helps show where Jun Peng may publish in the future.
Co-authorship network of co-authors of Jun Peng
This figure shows the co-authorship network connecting the top 25 collaborators of Jun Peng. A scholar is included among the top collaborators of Jun Peng 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 Peng. Jun Peng is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 0 | |
| 7 | 0 | |
| 8 | 32 | |
| 9 | 0 | |
| 10 | 1 | |
| 11 | 1 | |
| 12 | 一种基于TOPSIS的卫星资源选择模型 (TOPSIS Based Model for Satellite Resource Selection). | 1 |
| 13 | 1 | |
| 14 | 1 | |
| 15 | Application of Web usage mining based on improved genetic algorithm | 1 |
| 16 | Security Policy Conflict Detection and Resolution Based on Multidimensional Integer Space | 1 |
| 17 | 33 | |
| 18 | Model Checking of Wireless Authentication Protocol Linear MAKEP | 0 |
| 19 | 10 | |
| 20 | 6 |
About Jun Peng
Jun Peng is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mathematics, having authored 170 papers that have together received 1.1k indexed citations. Recurring topics across this work include Chaos-based Image/Signal Encryption (23 papers), Neural Networks and Applications (12 papers) and Chaos control and synchronization (12 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (255 citations), Artificial Intelligence (271 citations) and Control and Systems Engineering (192 citations). Jun Peng has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Kincho H. Law, Shangzhu Jin, Shuai Tan, Fuli Wang, Yuqing Chang, Zuojin Li, Liukui Chen, Ying Wu, Xiaofeng Liao and Du Zhang. Their work appears in journals such as Journal of Cleaner Production, Scientific Reports and IEEE Journal on Selected Areas in Communications.
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.