Natsuki Ueno
Impact in
- Signal Processing top 5%
- Speech and Audio Processing
- Cognitive Neuroscience top 10%
- Hearing Loss and Rehabilitation
Papers in
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- Acoustic Wave Phenomena Research 21
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- Speech and Audio Processing 23
- Co-authors
- Shoichi Koyama (27 shared papers)Hiroshi Saruwatari (23 shared papers)Makoto Kaneko (7 shared papers)Mikhail Svinin (3 shared papers)Hayato Ito (4 shared papers)Morito Akiyama (4 shared papers)Toshio Okada (2 shared papers)Toshihiro Kamohara (1 shared paper)
In The Last Decade
Natsuki Ueno
54 papers receiving 565 citations
Peers
Comparison fields: 5 of 55
- Signal Processing 233
- Cognitive Neuroscience 140
- Computational Mechanics 129
- Biomedical Engineering 262
- Computer Vision and Pattern Recognition 65
Countries citing papers authored by Natsuki Ueno
This map shows the geographic impact of Natsuki Ueno'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 Natsuki Ueno with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Natsuki Ueno more than expected).
Fields of papers citing papers by Natsuki Ueno
This network shows the impact of papers produced by Natsuki Ueno. 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 Natsuki Ueno. The network helps show where Natsuki Ueno may publish in the future.
Co-authors
The 25 scholars most cited alongside Natsuki Ueno, 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 58 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2017 | 66 | |
| 2 | 2007 | 60 | |
| 3 | 2018 | 39 | |
| 4 | 1998 | 38 | |
| 5 | 1981 | 34 | |
| 6 | 2019 | 31 | |
| 7 | 2021 | 30 | |
| 8 | 2021 | 20 | |
| 9 | 2002 | 18 | |
| 10 | 2019 | 17 | |
| 11 | 2005 | 15 | |
| 12 | 2022 | 14 | |
| 13 | 2024 | 14 | |
| 14 | 2020 | 14 | |
| 15 | 1988 | 12 | |
| 16 | 2002 | 12 | |
| 17 | 2022 | 11 | |
| 18 | 2022 | 10 | |
| 19 | 2021 | 10 | |
| 20 | 2002 | 8 |
About Natsuki Ueno
Natsuki Ueno is a scholar working on Biomedical Engineering, Signal Processing, Computational Mechanics, Cognitive Neuroscience and Electrical and Electronic Engineering, having authored 58 papers that have together received 592 indexed citations. Recurring topics across this work include Speech and Audio Processing (23 papers), Acoustic Wave Phenomena Research (21 papers), Advanced Adaptive Filtering Techniques (9 papers), Hearing Loss and Rehabilitation (9 papers), Structural Health Monitoring Techniques (5 papers), Distributed Sensor Networks and Detection Algorithms (4 papers), Aerodynamics and Acoustics in Jet Flows (4 papers) and Semiconductor Lasers and Optical Devices (4 papers). The work is most often cited by research in Signal Processing (233 citations), Cognitive Neuroscience (140 citations), Computational Mechanics (129 citations), Biomedical Engineering (262 citations) and Computer Vision and Pattern Recognition (65 citations). Natsuki Ueno has collaborated with scholars based in Japan, Germany and Italy. Frequent co-authors include Shoichi Koyama, Hiroshi Saruwatari, Makoto Kaneko, Mikhail Svinin, Hayato Ito, Morito Akiyama, Toshio Okada, Toshihiro Kamohara, Keiko Nishikubo and Osamu Fukuda. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Journal of Materials Science, IEEE Transactions on Signal Processing, Scientific Reports and Journal of the Audio Engineering Society.
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.