Tsuyoshi Ueyama
- Control and Systems Engineering top 10%
- Computer Vision and Pattern Recognition top 10%
- Mechanical Engineering
- Industrial and Manufacturing Engineering top 5%
- Biomedical Engineering
- Co-authors
- Jun OtaRyosuke ChibaTamio AraiToshio FukudaYanjiang HuangFumihito AraiY. KawauchiHideaki Fujiwara
- Topics
- Advanced MRI Techniques and Applications (13 papers)Robotic Path Planning Algorithms (13 papers)Robot Manipulation and Learning (12 papers)
- Cited by
- Industrial and Manufacturing EngineeringControl and Systems EngineeringComputer Vision and Pattern Recognition
- Partner nations
- JapanUnited StatesSpain
In The Last Decade
Tsuyoshi Ueyama
51 papers receiving 353 citations
Peers
Comparison fields: 5 of 74
- Control and Systems Engineering 125
- Computer Vision and Pattern Recognition 110
- Mechanical Engineering 89
- Industrial and Manufacturing Engineering 74
- Biomedical Engineering 65
Countries citing papers authored by Tsuyoshi Ueyama
This map shows the geographic impact of Tsuyoshi Ueyama'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 Tsuyoshi Ueyama with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tsuyoshi Ueyama more than expected).
Fields of papers citing papers by Tsuyoshi Ueyama
This network shows the impact of papers produced by Tsuyoshi Ueyama. 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 Tsuyoshi Ueyama. The network helps show where Tsuyoshi Ueyama may publish in the future.
Co-authorship network of co-authors of Tsuyoshi Ueyama
This figure shows the co-authorship network connecting the top 25 collaborators of Tsuyoshi Ueyama. A scholar is included among the top collaborators of Tsuyoshi Ueyama 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 Tsuyoshi Ueyama. Tsuyoshi Ueyama is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 0 | |
| 5 | 9 | |
| 6 | 14 | |
| 7 | 0 | |
| 8 | 3 | |
| 9 | 37 | |
| 10 | 3 | |
| 11 | 1 | |
| 12 | 0 | |
| 13 | 0 | |
| 14 | 5 | |
| 15 | 7 | |
| 16 | 18 | |
| 17 | 5 | |
| 18 | 2 | |
| 19 | 5 | |
| 20 | 8 |
About Tsuyoshi Ueyama
Tsuyoshi Ueyama is a scholar working on Industrial and Manufacturing Engineering, Computer Vision and Pattern Recognition and Control and Systems Engineering, having authored 57 papers that have together received 374 indexed citations. Recurring topics across this work include Advanced MRI Techniques and Applications (13 papers), Robotic Path Planning Algorithms (13 papers) and Robot Manipulation and Learning (12 papers). The work is most often cited by research in Industrial and Manufacturing Engineering (74 citations), Control and Systems Engineering (125 citations) and Computer Vision and Pattern Recognition (110 citations). Tsuyoshi Ueyama has collaborated with scholars based in Japan, United States and Spain. Frequent co-authors include Jun Ota, Ryosuke Chiba, Tamio Arai, Toshio Fukuda, Yanjiang Huang, Fumihito Arai, Y. Kawauchi, Hideaki Fujiwara, Tetsuya Wakayama and Atsuomi Kimura. Their work appears in journals such as Circulation, Sensors and Frontiers in Pharmacology.
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.