Hirofumi Uemura
- Electrical and Electronic Engineering
- Computer Vision and Pattern Recognition top 5%
- Artificial Intelligence
- Control and Systems Engineering
- Biomedical Engineering
- Co-authors
- Krystian MikolajczykJohann W. KolarDominik BortisO. ApeldoornGabriel OrtizShota IshikawaFlorian KrismerRalph M. Burkart
- Topics
- Advanced DC-DC Converters (7 papers)Silicon Carbide Semiconductor Technologies (7 papers)Multilevel Inverters and Converters (5 papers)
- Cited by
- Computer Vision and Pattern RecognitionElectrical and Electronic EngineeringHuman-Computer Interaction
- Journals
- IEEE Transactions on Electron DevicesComputer Vision and Image UnderstandingIEEJ Journal of Industry Applications
- Partner nations
- JapanSwitzerlandUnited Kingdom
In The Last Decade
Hirofumi Uemura
16 papers receiving 419 citations
Peers
Comparison fields: 5 of 31
- Electrical and Electronic Engineering 240
- Computer Vision and Pattern Recognition 185
- Artificial Intelligence 74
- Control and Systems Engineering 56
- Biomedical Engineering 31
Countries citing papers authored by Hirofumi Uemura
This map shows the geographic impact of Hirofumi Uemura'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 Hirofumi Uemura with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hirofumi Uemura more than expected).
Fields of papers citing papers by Hirofumi Uemura
This network shows the impact of papers produced by Hirofumi Uemura. 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 Hirofumi Uemura. The network helps show where Hirofumi Uemura may publish in the future.
Co-authorship network of co-authors of Hirofumi Uemura
This figure shows the co-authorship network connecting the top 25 collaborators of Hirofumi Uemura. A scholar is included among the top collaborators of Hirofumi Uemura based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Hirofumi Uemura. Hirofumi Uemura is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 41 | |
| 7 | 22 | |
| 8 | 31 | |
| 9 | 105 | |
| 10 | 20 | |
| 11 | 19 | |
| 12 | Multiple Feature Points Tracking for Camera Motion Compensation | 0 |
| 13 | 118 | |
| 14 | 51 | |
| 15 | 7 | |
| 16 | 6 | |
| 17 | A Study on a Human-Oriented Compensator for the Human-Machine System | 1 |
| 18 | 6 |
About Hirofumi Uemura
Hirofumi Uemura is a scholar working on Computer Vision and Pattern Recognition, Electrical and Electronic Engineering and Control and Systems Engineering, having authored 18 papers that have together received 437 indexed citations. Recurring topics across this work include Advanced DC-DC Converters (7 papers), Silicon Carbide Semiconductor Technologies (7 papers) and Multilevel Inverters and Converters (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (185 citations), Electrical and Electronic Engineering (240 citations) and Human-Computer Interaction (22 citations). Hirofumi Uemura has collaborated with scholars based in Japan, Switzerland and United Kingdom. Frequent co-authors include Krystian Mikolajczyk, Johann W. Kolar, Dominik Bortis, O. Apeldoorn, Gabriel Ortiz, Shota Ishikawa, Florian Krismer, Ralph M. Burkart, J. Mühlethaler and Yasuhiro Okuma. Their work appears in journals such as IEEE Transactions on Electron Devices, Computer Vision and Image Understanding and IEEJ Journal of Industry Applications.
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.