Siyuan Yang
- Computer Vision and Pattern Recognition top 5%
- Environmental Engineering top 5%
- Health, Toxicology and Mutagenesis top 10%
- Artificial Intelligence top 10%
- Economics and Econometrics top 10%
- Topics
- Environmental Impact and Sustainability (8 papers)Anomaly Detection Techniques and Applications (5 papers)Digital Media Forensic Detection (5 papers)
- Cited by
- Environmental EngineeringComputer Vision and Pattern RecognitionHealth, Toxicology and Mutagenesis
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceRemote Sensing of EnvironmentJournal of Cleaner Production
- Partner nations
- ChinaSingaporeUnited States
In The Last Decade
Siyuan Yang
35 papers receiving 617 citations
Peers
Comparison fields: 5 of 96
- Computer Vision and Pattern Recognition 201
- Environmental Engineering 158
- Health, Toxicology and Mutagenesis 126
- Artificial Intelligence 123
- Economics and Econometrics 88
Countries citing papers authored by Siyuan Yang
This map shows the geographic impact of Siyuan Yang'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 Siyuan Yang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Siyuan Yang more than expected).
Fields of papers citing papers by Siyuan Yang
This network shows the impact of papers produced by Siyuan Yang. 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 Siyuan Yang. The network helps show where Siyuan Yang may publish in the future.
Co-authorship network of co-authors of Siyuan Yang
This figure shows the co-authorship network connecting the top 25 collaborators of Siyuan Yang. A scholar is included among the top collaborators of Siyuan Yang 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 Siyuan Yang. Siyuan Yang 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 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 4 | |
| 6 | 10 | |
| 7 | 3 | |
| 8 | 4 | |
| 9 | 35 | |
| 10 | 34 | |
| 11 | 22 | |
| 12 | 1 | |
| 13 | 18 | |
| 14 | 71 | |
| 15 | 73 | |
| 16 | 17 | |
| 17 | 48 | |
| 18 | 1 | |
| 19 | 18 | |
| 20 | 7 |
About Siyuan Yang
Siyuan Yang is a scholar working on Environmental Engineering, Computer Vision and Pattern Recognition and Computer Graphics and Computer-Aided Design, having authored 38 papers that have together received 639 indexed citations. Recurring topics across this work include Environmental Impact and Sustainability (8 papers), Anomaly Detection Techniques and Applications (5 papers) and Digital Media Forensic Detection (5 papers). The work is most often cited by research in Environmental Engineering (158 citations), Computer Vision and Pattern Recognition (201 citations) and Health, Toxicology and Mutagenesis (126 citations). Siyuan Yang has collaborated with scholars based in China, Singapore and United States. Frequent co-authors include Bin Chen, Alex C. Kot, Brian D. Fath, Delin Fang, Bin Chen, Jun Liu, Shijian Lu, M.H. Er, Yao Zhao and Rongrong Ni. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Remote Sensing of Environment and Journal of Cleaner Production.
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.