Quan Wen
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Management Science and Operations Research top 2%
- Oncology
- Computational Theory and Mathematics top 5%
- Co-authors
- Yafei SongXiaodan WangM. Emre CelebiWenlong HuangSae HwangGerald SchaeferHitoshi IyatomiHang Chang
- Topics
- Advanced Image and Video Retrieval Techniques (10 papers)Domain Adaptation and Few-Shot Learning (9 papers)Multi-Criteria Decision Making (8 papers)
- Cited by
- Management Science and Operations ResearchComputer Vision and Pattern RecognitionArtificial Intelligence
- Partner nations
- ChinaUnited StatesIreland
In The Last Decade
Quan Wen
70 papers receiving 898 citations
Peers
Comparison fields: 5 of 107
- Artificial Intelligence 324
- Computer Vision and Pattern Recognition 284
- Management Science and Operations Research 232
- Oncology 153
- Computational Theory and Mathematics 96
Countries citing papers authored by Quan Wen
This map shows the geographic impact of Quan Wen'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 Quan Wen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Quan Wen more than expected).
Fields of papers citing papers by Quan Wen
This network shows the impact of papers produced by Quan Wen. 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 Quan Wen. The network helps show where Quan Wen may publish in the future.
Co-authorship network of co-authors of Quan Wen
This figure shows the co-authorship network connecting the top 25 collaborators of Quan Wen. A scholar is included among the top collaborators of Quan Wen 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 Quan Wen. Quan Wen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 2 | |
| 3 | 8 | |
| 4 | 10 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 32 | |
| 8 | 1 | |
| 9 | 37 | |
| 10 | Summary of feature selection algorithms | 33 |
| 11 | 5 | |
| 12 | Incremental training algorithm of SVM based on active learning | 2 |
| 13 | A Fast Image Matching Algorithm Based on Characteristic Points | 0 |
| 14 | 3 | |
| 15 | Concept drift on SVM incremental learning and its disposals | 0 |
| 16 | 1 | |
| 17 | 14 | |
| 18 | 0 | |
| 19 | 1 | |
| 20 | Identify Determinacy from Chaotic Time Series | 1 |
About Quan Wen
Quan Wen is a scholar working on Computer Vision and Pattern Recognition, Biophysics and Artificial Intelligence, having authored 79 papers that have together received 929 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (10 papers), Domain Adaptation and Few-Shot Learning (9 papers) and Multi-Criteria Decision Making (8 papers). The work is most often cited by research in Management Science and Operations Research (232 citations), Computer Vision and Pattern Recognition (284 citations) and Artificial Intelligence (324 citations). Quan Wen has collaborated with scholars based in China, United States and Ireland. Frequent co-authors include Yafei Song, Xiaodan Wang, M. Emre Celebi, Wenlong Huang, Sae Hwang, Gerald Schaefer, Hitoshi Iyatomi, Hang Chang, Bahram Parvin and Atul Sajjanhar. Their work appears in journals such as IEEE Access, Pattern Recognition and Plastic & Reconstructive Surgery.
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.