Yihong Chen
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence top 10%
- Electrical and Electronic Engineering
- Management, Monitoring, Policy and Law top 10%
- Aerospace Engineering
- Topics
- Topic Modeling (2 papers)Recommender Systems and Techniques (2 papers)Multimodal Machine Learning Applications (2 papers)
- Cited by
- Computer Vision and Pattern RecognitionArtificial IntelligenceManagement, Monitoring, Policy and Law
- Partner nations
- ChinaTaiwanUnited States
In The Last Decade
Yihong Chen
23 papers receiving 456 citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Computer Vision and Pattern Recognition 217
- Artificial Intelligence 156
- Electrical and Electronic Engineering 133
- Management, Monitoring, Policy and Law 45
- Aerospace Engineering 38
Countries citing papers authored by Yihong Chen
This map shows the geographic impact of Yihong 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 Yihong Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yihong Chen more than expected).
Fields of papers citing papers by Yihong Chen
This network shows the impact of papers produced by Yihong 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 Yihong Chen. The network helps show where Yihong Chen may publish in the future.
Co-authorship network of co-authors of Yihong Chen
This figure shows the co-authorship network connecting the top 25 collaborators of Yihong Chen. A scholar is included among the top collaborators of Yihong 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 Yihong Chen. Yihong 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 | 3 | |
| 2 | 1 | |
| 3 | All-ferroelectric implementation of reservoir computingbreakdown → | 121 |
| 4 | 5 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | LEARNABLE EMBEDDING SIZES FOR RECOMMENDER SYSTEMS | 1 |
| 9 | 0 | |
| 10 | RepPoints v2: Verification Meets Regression for Object Detection | 10 |
| 11 | 217 | |
| 12 | 3 | |
| 13 | 66 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 6 | |
| 17 | 5 | |
| 18 | 3 | |
| 19 | Path planning method design for mobile robots | 5 |
| 20 | 2 |
About Yihong Chen
Yihong Chen is a scholar working on Computational Mathematics, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 25 papers that have together received 468 indexed citations. Recurring topics across this work include Topic Modeling (2 papers), Recommender Systems and Techniques (2 papers) and Multimodal Machine Learning Applications (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (217 citations), Artificial Intelligence (156 citations) and Management, Monitoring, Policy and Law (45 citations). Yihong Chen has collaborated with scholars based in China, Taiwan and United States. Frequent co-authors include Liwei Wang, Han Hu, Yue Cao, Shuai Dong, Jun‐Ming Liu, Xingsen Gao, Min Zeng, Xubing Lu, Minghui Qin and Guofu Zhou. Their work appears in journals such as Nature Communications, Scientific Reports and Inorganic Chemistry.
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.