Qing Wu
- Control and Systems Engineering top 5%
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Molecular Biology
- Computer Networks and Communications top 10%
- Co-authors
- Shuai LiDechao ChenZeyu ChenXin LuoGang XuFaa‐Jeng LinHao LinLei Wang
- Topics
- Robotic Mechanisms and Dynamics (7 papers)Context-Aware Activity Recognition Systems (7 papers)IoT and Edge/Fog Computing (6 papers)
- Cited by
- Computational MathematicsComputer Vision and Pattern RecognitionControl and Systems Engineering
- Partner nations
- ChinaHong KongUnited Kingdom
In The Last Decade
Qing Wu
54 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 126
- Control and Systems Engineering 345
- Artificial Intelligence 325
- Computer Vision and Pattern Recognition 317
- Molecular Biology 140
- Computer Networks and Communications 128
Countries citing papers authored by Qing Wu
This map shows the geographic impact of Qing 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 Qing Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qing Wu more than expected).
Fields of papers citing papers by Qing Wu
This network shows the impact of papers produced by Qing 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 Qing Wu. The network helps show where Qing Wu may publish in the future.
Co-authorship network of co-authors of Qing Wu
This figure shows the co-authorship network connecting the top 25 collaborators of Qing Wu. A scholar is included among the top collaborators of Qing 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 Qing Wu. Qing 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 | 5 | |
| 3 | 41 | |
| 4 | 53 | |
| 5 | 7 | |
| 6 | 5 | |
| 7 | 23 | |
| 8 | 47 | |
| 9 | 63 | |
| 10 | 42 | |
| 11 | Improved Expressivity Through Dendritic Neural Networks. | 9 |
| 12 | The identification of Zwischgold and other metal foils on historical sculptures by handheld XRF spectrometry | 6 |
| 13 | 16 | |
| 14 | 22 | |
| 15 | 13 | |
| 16 | The Vehicle Fault Diagnosis Research Based on T-S Model Fuzzy Neural Network | 0 |
| 17 | 26 | |
| 18 | An adaptive requirement framework for SCUDW are middleware in ubiquitous computing | 1 |
| 19 | Trusted Component Model in Mobile Distributed Environment | 0 |
| 20 | Research and Application of a Trusted and Light Weight J2EE Framework | 0 |
About Qing Wu
Qing Wu is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Computer Networks and Communications, having authored 63 papers that have together received 1.2k indexed citations. Recurring topics across this work include Robotic Mechanisms and Dynamics (7 papers), Context-Aware Activity Recognition Systems (7 papers) and IoT and Edge/Fog Computing (6 papers). The work is most often cited by research in Computational Mathematics (10 citations), Computer Vision and Pattern Recognition (317 citations) and Control and Systems Engineering (345 citations). Qing Wu has collaborated with scholars based in China, Hong Kong and United Kingdom. Frequent co-authors include Shuai Li, Dechao Chen, Zeyu Chen, Xin Luo, Gang Xu, Faa‐Jeng Lin, Hao Lin, Lei Wang, Jinbo Xu and Tianming Zhou. Their work appears in journals such as Nucleic Acids Research, IEEE Access 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.