Shuichi Kurogi
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Plant Science
- Control and Systems Engineering
- Aerospace Engineering
- Co-authors
- Takeshi NishidaKazuya MatsuoHiroto SuharaMasakazu NakamuraToshirou NishidaYoshinori KawamuraTsutomu HattoriTian‐Chuan Hsu
- Topics
- Neural Networks and Applications (20 papers)Robotics and Sensor-Based Localization (8 papers)Insect-Plant Interactions and Control (7 papers)
In The Last Decade
Shuichi Kurogi
48 papers receiving 193 citations
Peers
Comparison fields: 5 of 60
- Artificial Intelligence 56
- Computer Vision and Pattern Recognition 53
- Plant Science 52
- Control and Systems Engineering 40
- Aerospace Engineering 31
Countries citing papers authored by Shuichi Kurogi
This map shows the geographic impact of Shuichi Kurogi'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 Shuichi Kurogi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Shuichi Kurogi more than expected).
Fields of papers citing papers by Shuichi Kurogi
This network shows the impact of papers produced by Shuichi Kurogi. 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 Shuichi Kurogi. The network helps show where Shuichi Kurogi may publish in the future.
Co-authorship network of co-authors of Shuichi Kurogi
This figure shows the co-authorship network connecting the top 25 collaborators of Shuichi Kurogi. A scholar is included among the top collaborators of Shuichi Kurogi 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 Shuichi Kurogi. Shuichi Kurogi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 11 | |
| 3 | 4 | |
| 4 | 5 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | Tracking and shape estimation of deformable object using particle filter and adaptive vector quantizer | 0 |
| 8 | 3 | |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 4 | |
| 14 | A Multi-Layered Competitive Net for Pattern Recognition Invariant to Coordinate Transformations | 1 |
| 15 | An Analysis of Competitive Associative Nets. | 2 |
| 16 | Learning Algorithms Using Firing Numbers of Weight Vectors for WTA Networks in Rotation Invariant Pattern Classification | 3 |
| 17 | 0 | |
| 18 | Neuro-Controllers Using Competitive Associative Nets Requiring Neither Parameterization of Plants nor Special Training | 1 |
| 19 | 11 | |
| 20 | 14 |
About Shuichi Kurogi
Shuichi Kurogi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Insect Science, having authored 57 papers that have together received 218 indexed citations. Recurring topics across this work include Neural Networks and Applications (20 papers), Robotics and Sensor-Based Localization (8 papers) and Insect-Plant Interactions and Control (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (53 citations), Insect Science (29 citations) and Signal Processing (20 citations). Shuichi Kurogi has collaborated with scholars based in Japan, Taiwan and China. Frequent co-authors include Takeshi Nishida, Kazuya Matsuo, Hiroto Suhara, Masakazu Nakamura, Toshirou Nishida, Yoshinori Kawamura, Tsutomu Hattori, Tian‐Chuan Hsu, Kenji Suetsugu and Yasuhiro Watanabe. Their work appears in journals such as Neurocomputing, Mycologia and Biological Cybernetics.
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.