Hongmei Yan
- Human-Computer Interaction top 5%
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- Visual Attention and Saliency Detection 12
- Cognitive Neuroscience top 10%
- Visual perception and processing mechanisms 18
- Neural dynamics and brain function 10
- Face Recognition and Perception 8
- Neural and Behavioral Psychology Studies 6
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- Multisensory perception and integration 7
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- Cell Image Analysis Techniques 5
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- Liver Disease Diagnosis and Treatment 5
- Co-authors
- Tao DengYongjie LiKai-Fu YangLong QinXiang GaoHong‐Jin SunWei HuangJun Zheng
- Cited by
- Human-Computer InteractionComputer Vision and Pattern RecognitionHealth Information Management
- Journals
- SHILAP Revista de lepidopterología (1 paper)PLoS ONE (3 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (1 paper)
- Partner nations
- ChinaUnited StatesBelgium
In The Last Decade
Hongmei Yan
58 papers receiving 787 citations
Peers
Comparison fields: 5 of 110
- Human-Computer Interaction 90
- Computer Vision and Pattern Recognition 282
- Health Information Management 63
- Cognitive Neuroscience 232
- Experimental and Cognitive Psychology 84
Countries citing papers authored by Hongmei Yan
This map shows the geographic impact of Hongmei 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 Hongmei Yan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hongmei Yan more than expected).
Fields of papers citing papers by Hongmei Yan
This network shows the impact of papers produced by Hongmei 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 Hongmei Yan. The network helps show where Hongmei Yan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Hongmei 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
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 0 | |
| 2 | 2024 | 0 | |
| 3 | 2024 | 2 | |
| 4 | 2024 | 3 | |
| 5 | 2023 | 5 | |
| 6 | 2021 | 14 | |
| 7 | 2021 | 3 | |
| 8 | 2020 | 11 | |
| 9 | 2020 | 10 | |
| 10 | 2019 | 8 | |
| 11 | 2019 | 11 | |
| 12 | 2017 | 2 | |
| 13 | 2017 | 80 | |
| 14 | 2015 | 7 | |
| 15 | 2015 | 3 | |
| 16 | 2014 | 6 | |
| 17 | 2011 | 10 | |
| 18 | Adsorbability of active carbon fiber for gaseous benzene. | 2009 | 1 |
| 19 | Insulin sensitizers in treatment of nonalcoholic fatty liver disease. | 2009 | 0 |
| 20 | 2003 | 17 |
About Hongmei Yan
Hongmei Yan is a scholar working on Cognitive Neuroscience, Computer Vision and Pattern Recognition and Biophysics, having authored 64 papers that have together received 808 indexed citations. Recurring topics across this work include Visual perception and processing mechanisms (18 papers), Visual Attention and Saliency Detection (12 papers), Neural dynamics and brain function (10 papers), Face Recognition and Perception (8 papers), Multisensory perception and integration (7 papers), Neural and Behavioral Psychology Studies (6 papers), Cell Image Analysis Techniques (5 papers) and Liver Disease Diagnosis and Treatment (5 papers). The work is most often cited by research in Human-Computer Interaction (90 citations), Computer Vision and Pattern Recognition (282 citations) and Health Information Management (63 citations). Hongmei Yan has collaborated with scholars based in China, United States and Belgium. Frequent co-authors include Tao Deng, Yongjie Li, Kai-Fu Yang, Long Qin, Xiang Gao, Hong‐Jin Sun, Wei Huang, Jun Zheng, Yingtao Jiang and Huafu Chen. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and IEEE Transactions on Pattern Analysis and Machine 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.