Chengchao Shen
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 5%
- Radiology, Nuclear Medicine and Imaging
- Electrical and Electronic Engineering
- Atomic and Molecular Physics, and Optics
- Co-authors
- Mingli SongJie SongXinchao WangYang LiuYezhou YangLi SunSihui LuoJie Guang Song
- Topics
- Domain Adaptation and Few-Shot Learning (9 papers)Iron-based superconductors research (5 papers)Advanced Neural Network Applications (4 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Chengchao Shen
22 papers receiving 415 citations
Peers
Comparison fields: 5 of 67
- Artificial Intelligence 276
- Computer Vision and Pattern Recognition 218
- Radiology, Nuclear Medicine and Imaging 44
- Electrical and Electronic Engineering 39
- Atomic and Molecular Physics, and Optics 37
Countries citing papers authored by Chengchao Shen
This map shows the geographic impact of Chengchao 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 Chengchao Shen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chengchao Shen more than expected).
Fields of papers citing papers by Chengchao Shen
This network shows the impact of papers produced by Chengchao 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 Chengchao Shen. The network helps show where Chengchao Shen may publish in the future.
Co-authorship network of co-authors of Chengchao Shen
This figure shows the co-authorship network connecting the top 25 collaborators of Chengchao Shen. A scholar is included among the top collaborators of Chengchao 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 Chengchao Shen. Chengchao 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 | 0 | |
| 2 | 1 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 12 | |
| 7 | 0 | |
| 8 | 14 | |
| 9 | 23 | |
| 10 | 35 | |
| 11 | Cloud-based interactive database management suite integrated with deep learning-based annotation tool for landslide mapping | 2 |
| 12 | 13 | |
| 13 | 6 | |
| 14 | 34 | |
| 15 | 0 | |
| 16 | 4 | |
| 17 | 3 | |
| 18 | 6 | |
| 19 | 13 | |
| 20 | 39 |
About Chengchao Shen
Chengchao Shen is a scholar working on Condensed Matter Physics, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 25 papers that have together received 421 indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (9 papers), Iron-based superconductors research (5 papers) and Advanced Neural Network Applications (4 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (218 citations), Artificial Intelligence (276 citations) and Media Technology (20 citations). Chengchao Shen has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Mingli Song, Jie Song, Xinchao Wang, Yang Liu, Yezhou Yang, Li Sun, Sihui Luo, Li Sun, Jie Guang Song and Gongfan Fang. Their work appears in journals such as Applied Physics Letters, Physical Review B 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.