Yuncheng Li
- Computer Vision and Pattern Recognition top 2%
- Artificial Intelligence top 2%
- Biomedical Engineering
- Signal Processing top 10%
- Human-Computer Interaction top 5%
- Topics
- Advanced Image and Video Retrieval Techniques (8 papers)Human Pose and Action Recognition (5 papers)Multimodal Machine Learning Applications (5 papers)
- Journals
- IEEE Transactions on Image ProcessingPattern RecognitionIEEE Transactions on Circuits and Systems for Video Technology
- Partner nations
- United StatesChina
In The Last Decade
Yuncheng Li
20 papers receiving 917 citations
Hit Papers
Peers
Comparison fields: 5 of 98
- Computer Vision and Pattern Recognition 619
- Artificial Intelligence 489
- Biomedical Engineering 161
- Signal Processing 70
- Human-Computer Interaction 67
Countries citing papers authored by Yuncheng Li
This map shows the geographic impact of Yuncheng Li'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 Yuncheng Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yuncheng Li more than expected).
Fields of papers citing papers by Yuncheng Li
This network shows the impact of papers produced by Yuncheng Li. 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 Yuncheng Li. The network helps show where Yuncheng Li may publish in the future.
Co-authorship network of co-authors of Yuncheng Li
This figure shows the co-authorship network connecting the top 25 collaborators of Yuncheng Li. A scholar is included among the top collaborators of Yuncheng Li 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 Yuncheng Li. Yuncheng Li 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 | 15 | |
| 4 | 1 | |
| 5 | 6 | |
| 6 | 31 | |
| 7 | 137 | |
| 8 | Learning from Noisy Labels with Distillationbreakdown → | 291 |
| 9 | 48 | |
| 10 | 88 | |
| 11 | 114 | |
| 12 | 5 | |
| 13 | Asynchronous Parallel Stochastic Gradient for Nonconvex Optimization | 107 |
| 14 | 5 | |
| 15 | 1 | |
| 16 | 7 | |
| 17 | 5 | |
| 18 | A general framework for recognizing complex events in Markov logic | 2 |
| 19 | 16 | |
| 20 | 4 |
About Yuncheng Li
Yuncheng Li is a scholar working on Computer Vision and Pattern Recognition, Communication and Artificial Intelligence, having authored 21 papers that have together received 953 indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (8 papers), Human Pose and Action Recognition (5 papers) and Multimodal Machine Learning Applications (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (619 citations), Artificial Intelligence (489 citations) and Human-Computer Interaction (67 citations). Yuncheng Li has collaborated with scholars based in United States and China. Frequent co-authors include Jiebo Luo, Shuicheng Yan, Liangliang Cao, Yale Song, Li-Jia Li, Zhengyuan Yang, Yang Feng, Yijun Huang, Ji Liu and Xiangru Lian. Their work appears in journals such as IEEE Transactions on Image Processing, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.
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.