Hongjun Song
- Aerospace Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Biomedical Engineering
- Artificial Intelligence
- Statistical and Nonlinear Physics
- Topics
- Advanced SAR Imaging Techniques (16 papers)Synthetic Aperture Radar (SAR) Applications and Techniques (14 papers)Image Enhancement Techniques (6 papers)
- Cited by
- Aerospace EngineeringComputer Vision and Pattern RecognitionStatistical and Nonlinear Physics
- Partner nations
- ChinaUnited States
In The Last Decade
Hongjun Song
34 papers receiving 414 citations
Peers
Comparison fields: 5 of 58
- Aerospace Engineering 208
- Computer Vision and Pattern Recognition 163
- Biomedical Engineering 53
- Artificial Intelligence 46
- Statistical and Nonlinear Physics 36
Countries citing papers authored by Hongjun Song
This map shows the geographic impact of Hongjun Song'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 Hongjun Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongjun Song more than expected).
Fields of papers citing papers by Hongjun Song
This network shows the impact of papers produced by Hongjun Song. 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 Hongjun Song. The network helps show where Hongjun Song may publish in the future.
Co-authorship network of co-authors of Hongjun Song
This figure shows the co-authorship network connecting the top 25 collaborators of Hongjun Song. A scholar is included among the top collaborators of Hongjun Song 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 Hongjun Song. Hongjun Song 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 | 6 | |
| 3 | 10 | |
| 4 | 19 | |
| 5 | 10 | |
| 6 | 1 | |
| 7 | 13 | |
| 8 | 1 | |
| 9 | 110 | |
| 10 | 60 | |
| 11 | 7 | |
| 12 | 4 | |
| 13 | 5 | |
| 14 | 4 | |
| 15 | Path planning method for mobile robot based on a hybrid learning approach | 0 |
| 16 | 1 | |
| 17 | 32 | |
| 18 | Optimization of PRF Selection in Spotlight SAR System Design | 1 |
| 19 | 18 | |
| 20 | Control structures for software agents | 1 |
About Hongjun Song
Hongjun Song is a scholar working on Aerospace Engineering, Leadership and Management and Computer Vision and Pattern Recognition, having authored 39 papers that have together received 424 indexed citations. Recurring topics across this work include Advanced SAR Imaging Techniques (16 papers), Synthetic Aperture Radar (SAR) Applications and Techniques (14 papers) and Image Enhancement Techniques (6 papers). The work is most often cited by research in Aerospace Engineering (208 citations), Computer Vision and Pattern Recognition (163 citations) and Statistical and Nonlinear Physics (36 citations). Hongjun Song has collaborated with scholars based in China and United States. Frequent co-authors include Ping Liu, Leyuan Wang, Robert Wang, Jiahuan Zhang, Fengjun Zhao, Yunkai Deng, Xu Zheng, Yunkai Deng, Bingji Zhao and Xiaolei Han. Their work appears in journals such as Communications of the ACM, IEEE Transactions on Geoscience and Remote Sensing and Sensors.
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.