He Yan
Impact in
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- Nonlinear Waves and Solitons
- Nonlinear Photonic Systems
- Modeling and Simulation top 5%
- Fractional Differential Equations Solutions
Papers in
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- Face and Expression Recognition 11
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- Machine Learning and ELM 8
- Co-authors
- Jian-Guo Liu (5 shared papers)Dong‐Jun Yu (15 shared papers)Qiaolin Ye (12 shared papers)Tian’an Zhang (5 shared papers)Li Zhou (2 shared papers)Liyong Fu (5 shared papers)Yiqing Xu (2 shared papers)Yong Qi (6 shared papers)
- Journals
- Knowledge-Based Systems (3 papers)Journal of Chemical Information and Modeling (2 papers)Nonlinear Dynamics (2 papers)Pattern Recognition (2 papers)Applied Intelligence (1 paper)
- Partner nations
- ChinaUnited StatesAustralia
In The Last Decade
He Yan
60 papers receiving 826 citations
Peers
Comparison fields: 5 of 104
- Statistical and Nonlinear Physics 238
- Modeling and Simulation 82
- Computer Vision and Pattern Recognition 189
- Transportation 61
- Building and Construction 86
Countries citing papers authored by He Yan
This map shows the geographic impact of He Yan'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 He Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites He Yan more than expected).
Fields of papers citing papers by He Yan
This network shows the impact of papers produced by He Yan. 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 He Yan. The network helps show where He Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside He Yan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 103 | |
| 2 | 2017 | 91 | |
| 3 | 2018 | 89 | |
| 4 | 2018 | 66 | |
| 5 | 2017 | 44 | |
| 6 | 2017 | 30 | |
| 7 | 2018 | 25 | |
| 8 | 2021 | 24 | |
| 9 | 2020 | 24 | |
| 10 | 2019 | 23 | |
| 11 | 2017 | 21 | |
| 12 | 2018 | 21 | |
| 13 | 2020 | 18 | |
| 14 | 2022 | 18 | |
| 15 | 2017 | 16 | |
| 16 | 2024 | 16 | |
| 17 | 2021 | 16 | |
| 18 | 2015 | 14 | |
| 19 | 2021 | 12 | |
| 20 | 2017 | 12 |
About He Yan
He Yan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering and Building and Construction, having authored 73 papers that have together received 854 indexed citations. Recurring topics across this work include Face and Expression Recognition (11 papers), Machine Learning and ELM (8 papers), Traffic Prediction and Management Techniques (8 papers), Traffic control and management (7 papers), Nonlinear Waves and Solitons (7 papers), Transportation Planning and Optimization (5 papers), Sparse and Compressive Sensing Techniques (4 papers) and Nonlinear Photonic Systems (4 papers). The work is most often cited by research in Statistical and Nonlinear Physics (238 citations), Modeling and Simulation (82 citations), Computer Vision and Pattern Recognition (189 citations), Transportation (61 citations) and Building and Construction (86 citations). He Yan has collaborated with scholars based in China, United States and Australia. Frequent co-authors include Jian-Guo Liu, Dong‐Jun Yu, Qiaolin Ye, Tian’an Zhang, Li Zhou, Liyong Fu, Yiqing Xu, Yong Qi, Xia Yuan and Xu Ma. Their work appears in journals such as Knowledge-Based Systems, Journal of Chemical Information and Modeling, Nonlinear Dynamics, Pattern Recognition and Applied Intelligence.
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.