Chongqing Chen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Materials Chemistry
- Biomedical Engineering
- Aerospace Engineering
- Co-authors
- Dezhi HanChin‐Chen ChangXiang ShenMingming CuiHao WangJun WangFan YinGaofeng Luo
- Topics
- Multimodal Machine Learning Applications (14 papers)Advanced Image and Video Retrieval Techniques (13 papers)Domain Adaptation and Few-Shot Learning (10 papers)
In The Last Decade
Chongqing Chen
22 papers receiving 588 citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Computer Vision and Pattern Recognition 222
- Artificial Intelligence 168
- Materials Chemistry 59
- Biomedical Engineering 57
- Aerospace Engineering 46
Countries citing papers authored by Chongqing Chen
This map shows the geographic impact of Chongqing Chen'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 Chongqing Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chongqing Chen more than expected).
Fields of papers citing papers by Chongqing Chen
This network shows the impact of papers produced by Chongqing Chen. 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 Chongqing Chen. The network helps show where Chongqing Chen may publish in the future.
Co-authorship network of co-authors of Chongqing Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Chongqing Chen. A scholar is included among the top collaborators of Chongqing Chen 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 Chongqing Chen. Chongqing Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 0 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 39 | |
| 6 | 4 | |
| 7 | 84 | |
| 8 | 1 | |
| 9 | MPCCT: Multimodal vision-language learning paradigm with context-based compact Transformerbreakdown → | 96 |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 21 | |
| 13 | NAS-YOLOX: a SAR ship detection using neural architecture search and multi-scale attentionbreakdown → | 111 |
| 14 | 0 | |
| 15 | 7 | |
| 16 | 15 | |
| 17 | 12 | |
| 18 | 23 | |
| 19 | 53 | |
| 20 | 40 |
About Chongqing Chen
Chongqing Chen is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Biochemistry, having authored 25 papers that have together received 599 indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (14 papers), Advanced Image and Video Retrieval Techniques (13 papers) and Domain Adaptation and Few-Shot Learning (10 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (222 citations), Artificial Intelligence (168 citations) and Modeling and Simulation (23 citations). Chongqing Chen has collaborated with scholars based in China, Taiwan and Australia. Frequent co-authors include Dezhi Han, Chin‐Chen Chang, Dezhi Han, Xiang Shen, Mingming Cui, Hao Wang, Jun Wang, Fan Yin, Gaofeng Luo and Zihan Guo. Their work appears in journals such as PLoS ONE, Journal of Colloid and Interface Science and Expert Systems with Applications.
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.