En Yu
Impact in
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- Video Surveillance and Tracking Methods
- Human Pose and Action Recognition
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Advanced Vision and Imaging
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- Fire Detection and Safety Systems
Papers in
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- Video Surveillance and Tracking Methods 9
- Advanced Vision and Imaging 3
- Multimodal Machine Learning Applications 2
- Human Pose and Action Recognition 2
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- Semantic Web and Ontologies 1
- Natural Language Processing Techniques 1
- Co-authors
- Shoudong Han (4 shared papers)Hongwei Wang (2 shared papers)Zhuoling Li (5 shared papers)Wenbing Tao (4 shared papers)Sijia Chen (2 shared papers)Zeming Li (2 shared papers)Jinrong Yang (2 shared papers)Haohan Wang (1 shared paper)
- Journals
- IEEE Robotics and Automation Letters (2 papers)Fundamental Research (1 paper)Neurocomputing (1 paper)Frontiers in Plant Science (1 paper)IEEE Transactions on Multimedia (1 paper)
- Partner nations
- ChinaUnited StatesFrance
In The Last Decade
En Yu
12 papers receiving 296 citations
Peers
Comparison fields: 5 of 43
- Computer Vision and Pattern Recognition 266
- Safety, Risk, Reliability and Quality 56
- Aerospace Engineering 73
- Artificial Intelligence 53
- Automotive Engineering 18
Countries citing papers authored by En Yu
This map shows the geographic impact of En Yu'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 En Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites En Yu more than expected).
Fields of papers citing papers by En Yu
This network shows the impact of papers produced by En Yu. 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 En Yu. The network helps show where En Yu may publish in the future.
Co-authors
The 25 scholars most cited alongside En Yu, 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 | 2022 | 118 | |
| 2 | 2022 | 106 | |
| 3 | 2022 | 39 | |
| 4 | 2024 | 12 | |
| 5 | 2023 | 7 | |
| 6 | 2023 | 6 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 3 | |
| 9 | 2023 | 3 | |
| 10 | 2022 | 3 | |
| 11 | 2024 | 1 | |
| 12 | 2025 | 1 | |
| 13 | 2025 | 0 | |
| 14 | 2025 | 0 | |
| 15 | 2024 | 0 |
About En Yu
En Yu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Biomedical Engineering, Safety, Risk, Reliability and Quality and Automotive Engineering, having authored 15 papers that have together received 303 indexed citations. Recurring topics across this work include Video Surveillance and Tracking Methods (9 papers), Advanced Vision and Imaging (3 papers), Fire Detection and Safety Systems (2 papers), Multimodal Machine Learning Applications (2 papers), Human Pose and Action Recognition (2 papers), Advanced Chemical Sensor Technologies (1 paper), Semantic Web and Ontologies (1 paper) and Natural Language Processing Techniques (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (266 citations), Safety, Risk, Reliability and Quality (56 citations), Aerospace Engineering (73 citations), Artificial Intelligence (53 citations) and Automotive Engineering (18 citations). En Yu has collaborated with scholars based in China, United States and France. Frequent co-authors include Shoudong Han, Hongwei Wang, Zhuoling Li, Wenbing Tao, Sijia Chen, Zeming Li, Jinrong Yang, Haohan Wang, Jinrong Yang and Haoqian Wang. Their work appears in journals such as IEEE Robotics and Automation Letters, Fundamental Research, Neurocomputing, Frontiers in Plant Science and IEEE Transactions on Multimedia.
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.