Yaqiang Wu
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Media Technology top 5%
- Information Systems
- Signal Processing
- Co-authors
- Lianwen JinQianying WangMingxiang CaiYuanzhi ZhuCanjie LuoXiaoxue ChenTianwei WangLele Xie
- Topics
- Handwritten Text Recognition Techniques (8 papers)Topic Modeling (3 papers)Vehicle License Plate Recognition (3 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Neural Networks and Learning SystemsIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Yaqiang Wu
12 papers receiving 338 citations
Peers
Comparison fields: 5 of 38
- Computer Vision and Pattern Recognition 288
- Artificial Intelligence 116
- Media Technology 96
- Information Systems 23
- Signal Processing 23
Countries citing papers authored by Yaqiang Wu
This map shows the geographic impact of Yaqiang 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 Yaqiang Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yaqiang Wu more than expected).
Fields of papers citing papers by Yaqiang Wu
This network shows the impact of papers produced by Yaqiang 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 Yaqiang Wu. The network helps show where Yaqiang Wu may publish in the future.
Co-authorship network of co-authors of Yaqiang Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Yaqiang Wu. A scholar is included among the top collaborators of Yaqiang 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 Yaqiang Wu. Yaqiang 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 | 0 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 0 | |
| 6 | 0 | |
| 7 | 6 | |
| 8 | 17 | |
| 9 | 5 | |
| 10 | 7 | |
| 11 | 20 | |
| 12 | 1 | |
| 13 | 36 | |
| 14 | 20 | |
| 15 | 161 | |
| 16 | 17 | |
| 17 | 1 | |
| 18 | 60 |
About Yaqiang Wu
Yaqiang Wu is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Media Technology, having authored 18 papers that have together received 351 indexed citations. Recurring topics across this work include Handwritten Text Recognition Techniques (8 papers), Topic Modeling (3 papers) and Vehicle License Plate Recognition (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (288 citations), Media Technology (96 citations) and Artificial Intelligence (116 citations). Yaqiang Wu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Lianwen Jin, Qianying Wang, Mingxiang Cai, Yuanzhi Zhu, Canjie Luo, Xiaoxue Chen, Tianwei Wang, Lele Xie, Sheng Zhang and Yuliang Liu. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Neural Networks and Learning Systems 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.