Ye Yan
Impact in
- Agronomy and Crop Science top 5%
- Crop Yield and Soil Fertility
- Cognitive Neuroscience top 10%
- EEG and Brain-Computer Interfaces
Papers in ⓘ
-
- Advanced Data Compression Techniques 6
- Advanced Vision and Imaging 5
- Co-authors
- Shanthini Sockanathan (4 shared papers)Jianwei Xu (3 shared papers)Feng Li (3 shared papers)Han Liu (2 shared papers)Lei Wang (2 shared papers)Erwei Yin (29 shared papers)Meenakshi Rao (1 shared paper)Pu Wang (5 shared papers)
- Journals
- Physical review. B. (4 papers)Journal of Neural Engineering (3 papers)Artificial Cells Nanomedicine and Biotechnology (3 papers)Nature Communications (2 papers)Field Crops Research (2 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Ye Yan
97 papers receiving 1.5k citations
Peers
Comparison fields: 5 of 148
- Agronomy and Crop Science 168
- Cognitive Neuroscience 160
- Human-Computer Interaction 44
- Plant Science 247
- Cellular and Molecular Neuroscience 116
Countries citing papers authored by Ye Yan
This map shows the geographic impact of Ye 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 Ye Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ye Yan more than expected).
Fields of papers citing papers by Ye Yan
This network shows the impact of papers produced by Ye 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 Ye Yan. The network helps show where Ye Yan may publish in the future.
Co-authors
The 25 scholars most cited alongside Ye 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 112 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 111 | |
| 2 | 2016 | 88 | |
| 3 | 2009 | 87 | |
| 4 | 2021 | 73 | |
| 5 | 2021 | 71 | |
| 6 | 2021 | 63 | |
| 7 | 2020 | 54 | |
| 8 | 2021 | 50 | |
| 9 | MAU: A Motion-Aware Unit for Video Prediction and Beyond | 2021 | 44 |
| 10 | 2017 | 44 | |
| 11 | 2015 | 43 | |
| 12 | 2007 | 42 | |
| 13 | 2019 | 42 | |
| 14 | 2020 | 36 | |
| 15 | 2021 | 34 | |
| 16 | 2021 | 34 | |
| 17 | 2012 | 31 | |
| 18 | 2020 | 30 | |
| 19 | 2023 | 28 | |
| 20 | 2021 | 28 |
About Ye Yan
Ye Yan is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience and Agronomy and Crop Science, having authored 112 papers that have together received 1.5k indexed citations. Recurring topics across this work include EEG and Brain-Computer Interfaces (10 papers), Neural dynamics and brain function (10 papers), Ferroelectric and Piezoelectric Materials (9 papers), Crop Yield and Soil Fertility (7 papers), Advanced Data Compression Techniques (6 papers), Video Coding and Compression Technologies (5 papers), Advanced Vision and Imaging (5 papers) and Multiferroics and related materials (5 papers). The work is most often cited by research in Agronomy and Crop Science (168 citations), Cognitive Neuroscience (160 citations), Human-Computer Interaction (44 citations), Plant Science (247 citations) and Cellular and Molecular Neuroscience (116 citations). Ye Yan has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Shanthini Sockanathan, Jianwei Xu, Feng Li, Han Liu, Lei Wang, Erwei Yin, Meenakshi Rao, Pu Wang, Liang Xie and Shoubing Huang. Their work appears in journals such as Physical review. B., Journal of Neural Engineering, Artificial Cells Nanomedicine and Biotechnology, Nature Communications and Field Crops Research.
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.