Qifan Wang
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 5%
- Plant Science
- Information Systems top 5%
- Biomedical Engineering
- Topics
- Advanced Image and Video Retrieval Techniques (12 papers)Image Retrieval and Classification Techniques (11 papers)Topic Modeling (10 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE Transactions on Pattern Analysis and Machine IntelligenceScientific Reports
- Partner nations
- United StatesChinaSingapore
In The Last Decade
Qifan Wang
61 papers receiving 925 citations
Hit Papers
Peers
Comparison fields: 5 of 110
- Computer Vision and Pattern Recognition 467
- Artificial Intelligence 234
- Plant Science 144
- Information Systems 112
- Biomedical Engineering 68
Countries citing papers authored by Qifan Wang
This map shows the geographic impact of Qifan Wang'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 Qifan Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Qifan Wang more than expected).
Fields of papers citing papers by Qifan Wang
This network shows the impact of papers produced by Qifan Wang. 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 Qifan Wang. The network helps show where Qifan Wang may publish in the future.
Co-authorship network of co-authors of Qifan Wang
This figure shows the co-authorship network connecting the top 25 collaborators of Qifan Wang. A scholar is included among the top collaborators of Qifan Wang 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 Qifan Wang. Qifan Wang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 12 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 0 | |
| 8 | 3 | |
| 9 | 9 | |
| 10 | 9 | |
| 11 | 7 | |
| 12 | 18 | |
| 13 | 11 | |
| 14 | 3 | |
| 15 | 55 | |
| 16 | 19 | |
| 17 | Learning to hash on partial multi-modal data | 19 |
| 18 | Ranking preserving hashing for fast similarity search | 36 |
| 19 | 52 | |
| 20 | Structural selection and testing of new yaw-inducing bursting layer | 1 |
About Qifan Wang
Qifan Wang is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Management Science and Operations Research, having authored 66 papers that have together received 945 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (12 papers), Image Retrieval and Classification Techniques (11 papers) and Topic Modeling (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (467 citations), Artificial Intelligence (234 citations) and Information Systems (112 citations). Qifan Wang has collaborated with scholars based in United States, China and Singapore. Frequent co-authors include Luo Si, Man Cheng, Zhenjiang Cai, Zhiwei Zhang, Hongbo Yuan, Liqi Yan, Siqi Ma, Dongfang Liu, Shuo Huang and Bin Shen. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and Scientific Reports.
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.