Yihui Fu
Impact in
- Signal Processing top 1%
- Speech and Audio Processing
- Music and Audio Processing
- Blind Source Separation Techniques
- Artificial Intelligence top 5%
- Speech Recognition and Synthesis
Papers in
-
- Speech and Audio Processing 11
- Music and Audio Processing 6
-
- Speech Recognition and Synthesis 8
- Topic Modeling 2
- Anomaly Detection Techniques and Applications 1
- Co-authors
- Lei Xie (6 shared papers)Shubo Lv (5 shared papers)Mengtao Xing (2 shared papers)Yanxin Hu (1 shared paper)Shimin Zhang (1 shared paper)Jian Wu (1 shared paper)Yun Liu (1 shared paper)Yannan Wang (3 shared papers)
- Journals
- 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE) (1 paper)ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (6 papers)
- Partner nations
- ChinaUnited StatesGermany
In The Last Decade
Yihui Fu
13 papers receiving 654 citations
Yihui Fu's Hit Papers
Peers
Comparison fields: 5 of 41
- Signal Processing 601
- Artificial Intelligence 441
- Computational Mechanics 220
- Pharmacy 19
- Cognitive Neuroscience 80
Countries citing papers authored by Yihui Fu
This map shows the geographic impact of Yihui Fu'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 Yihui Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yihui Fu more than expected).
Fields of papers citing papers by Yihui Fu
This network shows the impact of papers produced by Yihui Fu. 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 Yihui Fu. The network helps show where Yihui Fu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yihui Fu, 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 | DCCRN: Deep Complex Convolution Recurrent Network for Phase-Aware Speech Enhancement Hit paper breakdown → | 2020 | 461 |
| 2 | 2022 | 54 | |
| 3 | 2022 | 41 | |
| 4 | 2022 | 36 | |
| 5 | 2022 | 28 | |
| 6 | 2022 | 21 | |
| 7 | 2022 | 19 | |
| 8 | 2023 | 4 | |
| 9 | 2023 | 3 | |
| 10 | 2021 | 3 | |
| 11 | 2025 | 2 | |
| 12 | 2021 | 1 | |
| 13 | 2025 | 1 | |
| 14 | 2026 | 0 | |
| 15 | 2020 | 0 |
About Yihui Fu
Yihui Fu is a scholar working on Signal Processing, Artificial Intelligence, Computer Vision and Pattern Recognition, Mechanics of Materials and Cognitive Neuroscience, having authored 15 papers that have together received 674 indexed citations. Recurring topics across this work include Speech and Audio Processing (11 papers), Speech Recognition and Synthesis (8 papers), Music and Audio Processing (6 papers), Topic Modeling (2 papers), Data Quality and Management (1 paper), Handwritten Text Recognition Techniques (1 paper), Anomaly Detection Techniques and Applications (1 paper) and Infant Health and Development (1 paper). The work is most often cited by research in Signal Processing (601 citations), Artificial Intelligence (441 citations), Computational Mechanics (220 citations), Pharmacy (19 citations) and Cognitive Neuroscience (80 citations). Yihui Fu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Lei Xie, Shubo Lv, Mengtao Xing, Yanxin Hu, Shimin Zhang, Jian Wu, Yun Liu, Yannan Wang, Shiliang Zhang and Bin Ma. Their work appears in journals such as 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE) and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
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.