Kaoru Hiramatsu
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing top 5%
- Media Technology top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Kunio KashinoTakuhiro KanekoHirokazu KameokaXiaomeng WuNobukatsu HojoYusuke IjimaChihiro WatanabeXinhao Liu
- Topics
- Music and Audio Processing (5 papers)Data Management and Algorithms (5 papers)Advanced Image and Video Retrieval Techniques (4 papers)
- Partner nations
- JapanUnited Kingdom
In The Last Decade
Kaoru Hiramatsu
20 papers receiving 311 citations
Peers
Comparison fields: 5 of 55
- Artificial Intelligence 170
- Computer Vision and Pattern Recognition 142
- Signal Processing 142
- Media Technology 29
- Experimental and Cognitive Psychology 16
Countries citing papers authored by Kaoru Hiramatsu
This map shows the geographic impact of Kaoru Hiramatsu'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 Kaoru Hiramatsu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kaoru Hiramatsu more than expected).
Fields of papers citing papers by Kaoru Hiramatsu
This network shows the impact of papers produced by Kaoru Hiramatsu. 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 Kaoru Hiramatsu. The network helps show where Kaoru Hiramatsu may publish in the future.
Co-authorship network of co-authors of Kaoru Hiramatsu
This figure shows the co-authorship network connecting the top 25 collaborators of Kaoru Hiramatsu. A scholar is included among the top collaborators of Kaoru Hiramatsu 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 Kaoru Hiramatsu. Kaoru Hiramatsu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | 1 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | 39 | |
| 6 | 1 | |
| 7 | 25 | |
| 8 | 1 | |
| 9 | 52 | |
| 10 | 13 | |
| 11 | 65 | |
| 12 | 79 | |
| 13 | 0 | |
| 14 | 1 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | Exploring GeoMarkup on the Semantic Web | 2 |
| 18 | Project pervasive association : Toward acquiring situations in sensor networked environments | 4 |
| 19 | 0 | |
| 20 | Approximate Query Reformulation for Multiple Ontologies in the Semantic Web | 3 |
About Kaoru Hiramatsu
Kaoru Hiramatsu is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 25 papers that have together received 328 indexed citations. Recurring topics across this work include Music and Audio Processing (5 papers), Data Management and Algorithms (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). The work is most often cited by research in Signal Processing (142 citations), Computer Vision and Pattern Recognition (142 citations) and Artificial Intelligence (170 citations). Kaoru Hiramatsu has collaborated with scholars based in Japan and United Kingdom. Frequent co-authors include Kunio Kashino, Takuhiro Kaneko, Hirokazu Kameoka, Xiaomeng Wu, Nobukatsu Hojo, Yusuke Ijima, Chihiro Watanabe, Xinhao Liu, Go Irie and Hiroyasu Ando. Their work appears in journals such as International Journal of Computer Vision, Neurocomputing and Neural Networks.
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.