Pengcheng Shen
- Computer Vision and Pattern Recognition top 2%
- Signal Processing top 2%
- Artificial Intelligence top 10%
- Computational Mechanics top 10%
- Radiology, Nuclear Medicine and Imaging
- Topics
- Monoclonal and Polyclonal Antibodies Research (6 papers)Face recognition and analysis (5 papers)Protein purification and stability (5 papers)
- Journals
- Nature CommunicationsIEEE Transactions on Pattern Analysis and Machine IntelligenceIEEE Transactions on Signal Processing
- Partner nations
- ChinaBangladeshUnited States
In The Last Decade
Pengcheng Shen
26 papers receiving 695 citations
Hit Papers
Peers
Comparison fields: 5 of 83
- Computer Vision and Pattern Recognition 401
- Signal Processing 255
- Artificial Intelligence 165
- Computational Mechanics 126
- Radiology, Nuclear Medicine and Imaging 48
Countries citing papers authored by Pengcheng Shen
This map shows the geographic impact of Pengcheng Shen'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 Pengcheng Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pengcheng Shen more than expected).
Fields of papers citing papers by Pengcheng Shen
This network shows the impact of papers produced by Pengcheng Shen. 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 Pengcheng Shen. The network helps show where Pengcheng Shen may publish in the future.
Co-authorship network of co-authors of Pengcheng Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Pengcheng Shen. A scholar is included among the top collaborators of Pengcheng Shen 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 Pengcheng Shen. Pengcheng Shen 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 | 0 | |
| 3 | 0 | |
| 4 | 0 | |
| 5 | 2 | |
| 6 | 3 | |
| 7 | 1 | |
| 8 | 12 | |
| 9 | 3 | |
| 10 | 7 | |
| 11 | 1 | |
| 12 | 26 | |
| 13 | 29 | |
| 14 | 36 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 16 | |
| 18 | Distribution Distillation Loss: Generic Approach for Improving Face Recognition from Hard Samples | 1 |
| 19 | 35 | |
| 20 | CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognitionbreakdown → | 340 |
About Pengcheng Shen
Pengcheng Shen is a scholar working on Health Informatics, Signal Processing and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 712 indexed citations. Recurring topics across this work include Monoclonal and Polyclonal Antibodies Research (6 papers), Face recognition and analysis (5 papers) and Protein purification and stability (5 papers). The work is most often cited by research in Signal Processing (255 citations), Computer Vision and Pattern Recognition (401 citations) and Computational Mechanics (126 citations). Pengcheng Shen has collaborated with scholars based in China, Bangladesh and United States. Frequent co-authors include Chunguang Li, Shaoxin Li, Yuge Huang, Feiyue Huang, Jilin Li, Yuhan Wang, Xiaoming Liu, Ying Tai, Zhaoyang Zhang and Ying Liu. Their work appears in journals such as Nature Communications, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Signal Processing.
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.