Kota Yamaguchi
- Computer Vision and Pattern Recognition top 0.5%
- Artificial Intelligence top 5%
- Computational Mechanics top 5%
- Automotive Engineering top 10%
- Industrial and Manufacturing Engineering top 5%
- Co-authors
- Tamara L. BergLuis E. OrtizM. Hadi KiapourAlexander C. BergTorres BergMargaret MitchellAmit GoyalKarl Stratos
- Topics
- Advanced Image and Video Retrieval Techniques (10 papers)Generative Adversarial Networks and Image Synthesis (8 papers)Multimodal Machine Learning Applications (7 papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine IntelligenceInternational Journal of Computer VisionComputer Graphics Forum
- Partner nations
- JapanUnited StatesUnited Kingdom
In The Last Decade
Kota Yamaguchi
30 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 84
- Computer Vision and Pattern Recognition 1.4k
- Artificial Intelligence 461
- Computational Mechanics 201
- Automotive Engineering 119
- Industrial and Manufacturing Engineering 92
Countries citing papers authored by Kota Yamaguchi
This map shows the geographic impact of Kota Yamaguchi'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 Kota Yamaguchi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kota Yamaguchi more than expected).
Fields of papers citing papers by Kota Yamaguchi
This network shows the impact of papers produced by Kota Yamaguchi. 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 Kota Yamaguchi. The network helps show where Kota Yamaguchi may publish in the future.
Co-authorship network of co-authors of Kota Yamaguchi
This figure shows the co-authorship network connecting the top 25 collaborators of Kota Yamaguchi. A scholar is included among the top collaborators of Kota Yamaguchi 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 Kota Yamaguchi. Kota Yamaguchi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 6 | |
| 3 | 3 | |
| 4 | 1 | |
| 5 | 5 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 5 | |
| 9 | 9 | |
| 10 | 2 | |
| 11 | 22 | |
| 12 | 33 | |
| 13 | 81 | |
| 14 | 60 | |
| 15 | 176 | |
| 16 | 94 | |
| 17 | 251 | |
| 18 | Detecting Visual Text | 29 |
| 19 | 298 | |
| 20 | 6 |
About Kota Yamaguchi
Kota Yamaguchi is a scholar working on Computer Vision and Pattern Recognition, Computer Graphics and Computer-Aided Design and Computational Mechanics, having authored 31 papers that have together received 1.6k indexed citations. Recurring topics across this work include Advanced Image and Video Retrieval Techniques (10 papers), Generative Adversarial Networks and Image Synthesis (8 papers) and Multimodal Machine Learning Applications (7 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Museology (67 citations) and Artificial Intelligence (461 citations). Kota Yamaguchi has collaborated with scholars based in Japan, United States and United Kingdom. Frequent co-authors include Tamara L. Berg, Luis E. Ortiz, M. Hadi Kiapour, Alexander C. Berg, Torres Berg, Margaret Mitchell, Amit Goyal, Karl Stratos, Xufeng Han and Hal Daumé. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision and Computer Graphics Forum.
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.