Takeshi Maeda
- Computer Vision and Pattern Recognition top 5%
- Social Psychology top 10%
- Aerospace Engineering top 10%
- Control and Systems Engineering top 10%
- Artificial Intelligence
- Co-authors
- Hiroshi IshiguroEmanuele MenegattiTetsuo OnoMichita ImaiTakayuki KandaRyohei NakatsuSachio OgitaJunko Nishio
- Topics
- Social Robot Interaction and HRI (3 papers)Robotics and Automated Systems (2 papers)Robotic Path Planning Algorithms (2 papers)
In The Last Decade
Takeshi Maeda
11 papers receiving 314 citations
Peers
Comparison fields: 5 of 60
- Computer Vision and Pattern Recognition 165
- Social Psychology 124
- Aerospace Engineering 112
- Control and Systems Engineering 109
- Artificial Intelligence 70
Countries citing papers authored by Takeshi Maeda
This map shows the geographic impact of Takeshi Maeda'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 Takeshi Maeda with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Takeshi Maeda more than expected).
Fields of papers citing papers by Takeshi Maeda
This network shows the impact of papers produced by Takeshi Maeda. 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 Takeshi Maeda. The network helps show where Takeshi Maeda may publish in the future.
Co-authorship network of co-authors of Takeshi Maeda
This figure shows the co-authorship network connecting the top 25 collaborators of Takeshi Maeda. A scholar is included among the top collaborators of Takeshi Maeda 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 Takeshi Maeda. Takeshi Maeda 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 | 0 | |
| 3 | 2 | |
| 4 | An Optical Motion Capture System synchronized with GPS for Motion Analysis of Automobile Driver | 0 |
| 5 | TeamOSAKA A (Kid size) Team Description Paper | 3 |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 112 | |
| 9 | 13 | |
| 10 | Development of "Robovie" as platform of everyday-robot research | 8 |
| 11 | 184 | |
| 12 | 1 | |
| 13 | 8 | |
| 14 | 3 | |
| 15 | 1 | |
| 16 | 2 |
About Takeshi Maeda
Takeshi Maeda is a scholar working on Pharmacy, Computer Vision and Pattern Recognition and Critical Care and Intensive Care Medicine, having authored 16 papers that have together received 339 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (3 papers), Robotics and Automated Systems (2 papers) and Robotic Path Planning Algorithms (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (165 citations), Social Psychology (124 citations) and Human-Computer Interaction (31 citations). Takeshi Maeda has collaborated with scholars based in Japan, Italy and Indonesia. Frequent co-authors include Hiroshi Ishiguro, Emanuele Menegatti, Tetsuo Ono, Michita Imai, Takayuki Kanda, Ryohei Nakatsu, Sachio Ogita, Junko Nishio, Saburo Tsuji and Yuichiro Nakai. Their work appears in journals such as Brain Research, Robotics and Autonomous Systems and Acta Obstetricia Et Gynecologica Scandinavica.
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.