Fumihiko Ino
- Computer Vision and Pattern Recognition top 5%
- Computer Networks and Communications top 5%
- Hardware and Architecture top 5%
- Artificial Intelligence top 10%
- Radiology, Nuclear Medicine and Imaging
- Co-authors
- Kenichi HagiharaNoriyuki FujimotoA. TakeuchiT. OKUYAMAShinichi TamuraYoshinobu SatoYuki KotaniNariaki Fujimoto
- Topics
- Parallel Computing and Optimization Techniques (26 papers)Advanced Data Storage Technologies (17 papers)Distributed and Parallel Computing Systems (14 papers)
- Cited by
- Hardware and ArchitectureComputer Graphics and Computer-Aided DesignComputer Vision and Pattern Recognition
In The Last Decade
Fumihiko Ino
64 papers receiving 579 citations
Peers
Comparison fields: 5 of 67
- Computer Vision and Pattern Recognition 235
- Computer Networks and Communications 228
- Hardware and Architecture 192
- Artificial Intelligence 105
- Radiology, Nuclear Medicine and Imaging 85
Countries citing papers authored by Fumihiko Ino
This map shows the geographic impact of Fumihiko Ino'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 Fumihiko Ino with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fumihiko Ino more than expected).
Fields of papers citing papers by Fumihiko Ino
This network shows the impact of papers produced by Fumihiko Ino. 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 Fumihiko Ino. The network helps show where Fumihiko Ino may publish in the future.
Co-authorship network of co-authors of Fumihiko Ino
This figure shows the co-authorship network connecting the top 25 collaborators of Fumihiko Ino. A scholar is included among the top collaborators of Fumihiko Ino 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 Fumihiko Ino. Fumihiko Ino 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 | 3 | |
| 3 | 1 | |
| 4 | 0 | |
| 5 | 13 | |
| 6 | 4 | |
| 7 | 2 | |
| 8 | 10 | |
| 9 | 17 | |
| 10 | Improving Cache Locality for Ray Casting with CUDA | 3 |
| 11 | 3 | |
| 12 | 14 | |
| 13 | Vectorizing Mathematical Morphology Using the GPU | 1 |
| 14 | 11 | |
| 15 | 5 | |
| 16 | 3 | |
| 17 | 2 | |
| 18 | Evaluation of Performance Prediction Method for Master/Slave Parallel Programs | 0 |
| 19 | 16 | |
| 20 | 11 |
About Fumihiko Ino
Fumihiko Ino is a scholar working on Hardware and Architecture, Computer Graphics and Computer-Aided Design and Computational Mathematics, having authored 72 papers that have together received 598 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (26 papers), Advanced Data Storage Technologies (17 papers) and Distributed and Parallel Computing Systems (14 papers). The work is most often cited by research in Hardware and Architecture (192 citations), Computer Graphics and Computer-Aided Design (76 citations) and Computer Vision and Pattern Recognition (235 citations). Fumihiko Ino has collaborated with scholars based in Japan, China and Spain. Frequent co-authors include Kenichi Hagihara, Noriyuki Fujimoto, A. Takeuchi, T. OKUYAMA, Shinichi Tamura, Yoshinobu Sato, Yuki Kotani, Nariaki Fujimoto, Yasuyuki Matsushita and Toshihiko Sasama. Their work appears in journals such as BMC Bioinformatics, Knowledge-Based Systems and IEEE Transactions on Parallel and Distributed Systems.
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.