Fei Yuan
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Music and Audio Processing
-
- Emotion and Mood Recognition
Papers in
-
- Face and Expression Recognition 6
- Advanced Neural Network Applications 4
-
- Emotion and Mood Recognition 6
- Co-authors
- Hao Meng (9 shared papers)Tianhao Yan (4 shared papers)Hongwei Wei (2 shared papers)Hao Meng (4 shared papers)Qidan Zhu (2 shared papers)Jing Li (1 shared paper)Yili Xu (1 shared paper)Tao Zeng (1 shared paper)
- Journals
- IEEE Access (3 papers)IEEE Transactions on Industrial Informatics (1 paper)IEEE Transactions on Instrumentation and Measurement (1 paper)Multimedia Tools and Applications (1 paper)Arabian Journal for Science and Engineering (1 paper)
- Partner nations
- China
In The Last Decade
Fei Yuan
16 papers receiving 337 citations
Fei Yuan's Hit Papers
Peers
Comparison fields: 5 of 61
- Signal Processing 187
- Experimental and Cognitive Psychology 175
- Computer Vision and Pattern Recognition 71
- Artificial Intelligence 109
- Pharmacy 13
Countries citing papers authored by Fei Yuan
This map shows the geographic impact of Fei Yuan'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 Fei Yuan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fei Yuan more than expected).
Fields of papers citing papers by Fei Yuan
This network shows the impact of papers produced by Fei Yuan. 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 Fei Yuan. The network helps show where Fei Yuan may publish in the future.
Co-authors
The 10 scholars most cited alongside Fei Yuan, 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 | Speech Emotion Recognition From 3D Log-Mel Spectrograms With Deep Learning Network Hit paper breakdown → | 2019 | 261 |
| 2 | 2018 | 28 | |
| 3 | 2023 | 13 | |
| 4 | 2024 | 11 | |
| 5 | 2023 | 4 | |
| 6 | 2021 | 4 | |
| 7 | 2021 | 4 | |
| 8 | 2019 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2024 | 3 | |
| 11 | 2019 | 3 | |
| 12 | 2021 | 2 | |
| 13 | 2022 | 2 | |
| 14 | 2024 | 1 | |
| 15 | 2023 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2023 | 0 |
About Fei Yuan
Fei Yuan is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Urban Studies, Aerospace Engineering and Ocean Engineering, having authored 17 papers that have together received 345 indexed citations. Recurring topics across this work include Face and Expression Recognition (6 papers), Emotion and Mood Recognition (6 papers), Advanced Computing and Algorithms (4 papers), Advanced Neural Network Applications (4 papers), Infrared Target Detection Methodologies (3 papers), Hand Gesture Recognition Systems (2 papers), Gait Recognition and Analysis (2 papers) and Radiomics and Machine Learning in Medical Imaging (1 paper). The work is most often cited by research in Signal Processing (187 citations), Experimental and Cognitive Psychology (175 citations), Computer Vision and Pattern Recognition (71 citations), Artificial Intelligence (109 citations) and Pharmacy (13 citations). Fei Yuan has collaborated with scholars based in China. Frequent co-authors include Hao Meng, Tianhao Yan, Hongwei Wei, Hao Meng, Qidan Zhu, Jing Li, Yili Xu, Tao Zeng, Yimu Ji and Jing Li. Their work appears in journals such as IEEE Access, IEEE Transactions on Industrial Informatics, IEEE Transactions on Instrumentation and Measurement, Multimedia Tools and Applications and Arabian Journal for Science and Engineering.
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.