Pinhao Song
- Computer Vision and Pattern Recognition top 2%
- Ocean Engineering top 5%
- Water Science and Technology top 10%
- Oceanography top 10%
- Media Technology top 5%
- Co-authors
- Hong LiuLinhui DaiHao TangRunwei DingTao WangZhan ChenZhiwei WuTianyu Guo
- Topics
- Advanced Neural Network Applications (9 papers)Image Enhancement Techniques (5 papers)Underwater Vehicles and Communication Systems (4 papers)
- Journals
- Pattern RecognitionNeurocomputingIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- ChinaBelgiumUnited States
In The Last Decade
Pinhao Song
14 papers receiving 648 citations
Hit Papers
Peers
Comparison fields: 5 of 65
- Computer Vision and Pattern Recognition 506
- Ocean Engineering 125
- Water Science and Technology 108
- Oceanography 88
- Media Technology 87
Countries citing papers authored by Pinhao Song
This map shows the geographic impact of Pinhao 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 Pinhao Song with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pinhao Song more than expected).
Fields of papers citing papers by Pinhao Song
This network shows the impact of papers produced by Pinhao 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 Pinhao Song. The network helps show where Pinhao Song may publish in the future.
Co-authorship network of co-authors of Pinhao Song
This figure shows the co-authorship network connecting the top 25 collaborators of Pinhao Song. A scholar is included among the top collaborators of Pinhao 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 Pinhao Song. Pinhao 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 | 4 | |
| 2 | 23 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 51 | |
| 7 | Boosting R-CNN: Reweighting R-CNN samples by RPN’s error for underwater object detectionbreakdown → | 155 |
| 8 | 39 | |
| 9 | 4 | |
| 10 | 4 | |
| 11 | 36 | |
| 12 | 130 | |
| 13 | AO2-DETR: Arbitrary-Oriented Object Detection Transformerbreakdown → | 141 |
| 14 | 69 |
About Pinhao Song
Pinhao Song is a scholar working on Computer Vision and Pattern Recognition, Ocean Engineering and Media Technology, having authored 14 papers that have together received 666 indexed citations. Recurring topics across this work include Advanced Neural Network Applications (9 papers), Image Enhancement Techniques (5 papers) and Underwater Vehicles and Communication Systems (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (506 citations), Media Technology (87 citations) and Ocean Engineering (125 citations). Pinhao Song has collaborated with scholars based in China, Belgium and United States. Frequent co-authors include Hong Liu, Linhui Dai, Hao Tang, Runwei Ding, Tao Wang, Zhan Chen, Zhiwei Wu, Tao Wang, Tianyu Guo and Wei Shi. Their work appears in journals such as Pattern Recognition, Neurocomputing and IEEE Transactions on Circuits and Systems for Video Technology.
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.