Rui Dai
- Artificial Intelligence top 5%
- Computer Networks and Communications top 5%
- Computer Vision and Pattern Recognition top 5%
- Electrical and Electronic Engineering
- Signal Processing top 5%
- Co-authors
- Ian F. AkyildizSrijan DasDan TangFrançois BrémondPu WangLorenzo GarattoniGianpiero FrancescaXiong Li
- Topics
- Anomaly Detection Techniques and Applications (14 papers)Network Security and Intrusion Detection (10 papers)Human Pose and Action Recognition (9 papers)
- Cited by
- Computer Networks and CommunicationsArtificial IntelligenceComputer Vision and Pattern Recognition
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceSensorsFuzzy Sets and Systems
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
Rui Dai
40 papers receiving 846 citations
Peers
Comparison fields: 5 of 97
- Artificial Intelligence 426
- Computer Networks and Communications 342
- Computer Vision and Pattern Recognition 264
- Electrical and Electronic Engineering 121
- Signal Processing 105
Countries citing papers authored by Rui Dai
This map shows the geographic impact of Rui Dai'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 Rui Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rui Dai more than expected).
Fields of papers citing papers by Rui Dai
This network shows the impact of papers produced by Rui Dai. 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 Rui Dai. The network helps show where Rui Dai may publish in the future.
Co-authorship network of co-authors of Rui Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Rui Dai. A scholar is included among the top collaborators of Rui Dai 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 Rui Dai. Rui Dai is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 15 | |
| 2 | 10 | |
| 3 | 0 | |
| 4 | 4 | |
| 5 | 0 | |
| 6 | 54 | |
| 7 | 4 | |
| 8 | MS-TCT: Multi-Scale Temporal ConvTransformer for Action Detection | 2 |
| 9 | 10 | |
| 10 | 13 | |
| 11 | 30 | |
| 12 | 103 | |
| 13 | 20 | |
| 14 | 14 | |
| 15 | 48 | |
| 16 | 5 | |
| 17 | 15 | |
| 18 | 18 | |
| 19 | 3 | |
| 20 | 94 |
About Rui Dai
Rui Dai is a scholar working on Computer Networks and Communications, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 42 papers that have together received 866 indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (14 papers), Network Security and Intrusion Detection (10 papers) and Human Pose and Action Recognition (9 papers). The work is most often cited by research in Computer Networks and Communications (342 citations), Artificial Intelligence (426 citations) and Computer Vision and Pattern Recognition (264 citations). Rui Dai has collaborated with scholars based in China, United States and France. Frequent co-authors include Ian F. Akyildiz, Srijan Das, Dan Tang, François Brémond, Pu Wang, Lorenzo Garattoni, Gianpiero Francesca, Xiong Li, Yi Guan and Bin He. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Sensors and Fuzzy Sets and Systems.
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.