Song Wu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Media Technology
- Aerospace Engineering
- Biomedical Engineering
- Co-authors
- Erwin M. BakkerGuoqiang XiaoXinbo GaoNian ZhangMichael S. LewLi WangArd OerlemansJianhui Chen
- Topics
- Advanced Image and Video Retrieval Techniques (11 papers)Video Surveillance and Tracking Methods (10 papers)Multimodal Machine Learning Applications (7 papers)
- Cited by
- Computer Vision and Pattern RecognitionMedia TechnologyComputer Graphics and Computer-Aided Design
- Partner nations
- ChinaNetherlandsNew Zealand
In The Last Decade
Song Wu
20 papers receiving 281 citations
Peers
Comparison fields: 5 of 37
- Computer Vision and Pattern Recognition 267
- Artificial Intelligence 39
- Media Technology 24
- Aerospace Engineering 18
- Biomedical Engineering 10
Countries citing papers authored by Song Wu
This map shows the geographic impact of Song Wu'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 Song Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Song Wu more than expected).
Fields of papers citing papers by Song Wu
This network shows the impact of papers produced by Song Wu. 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 Song Wu. The network helps show where Song Wu may publish in the future.
Co-authorship network of co-authors of Song Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Song Wu. A scholar is included among the top collaborators of Song Wu 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 Song Wu. Song Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 5 | |
| 4 | 2 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 42 | |
| 8 | 0 | |
| 9 | 5 | |
| 10 | 1 | |
| 11 | 3 | |
| 12 | 9 | |
| 13 | 42 | |
| 14 | 32 | |
| 15 | 29 | |
| 16 | 10 | |
| 17 | 5 | |
| 18 | 58 | |
| 19 | 16 | |
| 20 | Face recognition based on Local Binary Patterns under difficult lighting condition | 2 |
About Song Wu
Song Wu is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computer Graphics and Computer-Aided Design, having authored 23 papers that have together received 289 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (11 papers), Video Surveillance and Tracking Methods (10 papers) and Multimodal Machine Learning Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (267 citations), Media Technology (24 citations) and Computer Graphics and Computer-Aided Design (7 citations). Song Wu has collaborated with scholars based in China, Netherlands and New Zealand. Frequent co-authors include Erwin M. Bakker, Guoqiang Xiao, Xinbo Gao, Nian Zhang, Michael S. Lew, Li Wang, Ard Oerlemans, Jianhui Chen, Zhenyang Yu and Michael S. Lew. Their work appears in journals such as Neurocomputing, Knowledge-Based Systems and Computer Vision and Image Understanding.
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.