Fang Dai
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 5%
- Computational Theory and Mathematics top 10%
- Ocean Engineering
- Electrical and Electronic Engineering
- Co-authors
- Peng XuWenyan GuoTing LiuRong ZhaoYuan WangNanning ZhengJianru XueGang Hu
- Topics
- Metaheuristic Optimization Algorithms Research (9 papers)Image and Signal Denoising Methods (4 papers)Advanced Algorithms and Applications (4 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceComputational Theory and Mathematics
- Journals
- Applied Soft ComputingPhysica A Statistical Mechanics and its ApplicationsSignal Processing
- Partner nations
- China
In The Last Decade
Fang Dai
28 papers receiving 351 citations
Peers
Comparison fields: 5 of 74
- Artificial Intelligence 191
- Computer Vision and Pattern Recognition 159
- Computational Theory and Mathematics 55
- Ocean Engineering 38
- Electrical and Electronic Engineering 35
Countries citing papers authored by Fang Dai
This map shows the geographic impact of Fang 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 Fang Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fang Dai more than expected).
Fields of papers citing papers by Fang Dai
This network shows the impact of papers produced by Fang 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 Fang Dai. The network helps show where Fang Dai may publish in the future.
Co-authorship network of co-authors of Fang Dai
This figure shows the co-authorship network connecting the top 25 collaborators of Fang Dai. A scholar is included among the top collaborators of Fang 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 Fang Dai. Fang 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 | 0 | |
| 2 | 2 | |
| 3 | 3 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 4 | |
| 8 | 24 | |
| 9 | 4 | |
| 10 | 3 | |
| 11 | 38 | |
| 12 | 90 | |
| 13 | 6 | |
| 14 | 4 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 32 |
About Fang Dai
Fang Dai is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Artificial Intelligence, having authored 31 papers that have together received 376 indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (9 papers), Image and Signal Denoising Methods (4 papers) and Advanced Algorithms and Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (159 citations), Artificial Intelligence (191 citations) and Computational Theory and Mathematics (55 citations). Fang Dai has collaborated with scholars based in China. Frequent co-authors include Peng Xu, Wenyan Guo, Ting Liu, Rong Zhao, Yuan Wang, Nanning Zheng, Jianru Xue, Ting Liu, Peng Xu and Gang Hu. Their work appears in journals such as Applied Soft Computing, Physica A Statistical Mechanics and its Applications and Signal Processing.
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.