Ryosuke Furuta

584 citations
29 papers · 272 · h-index 9

Impact in

Papers in

    • Advanced Vision and Imaging 6
    • Image Enhancement Techniques 5
    • Multimodal Machine Learning Applications 4
    • Human Pose and Action Recognition 4
    • Advanced Image and Video Retrieval Techniques 4
    • Video Analysis and Summarization 4
    • Video Surveillance and Tracking Methods 3

Ryosuke Furuta

24 papers receiving 260 citations

Peers

Ryosuke Furuta
Comparison fields: 5 of 63
  • Computer Vision and Pattern Recognition 126
  • Industrial and Manufacturing Engineering 57
  • Automotive Engineering 52
  • Health Informatics 4
  • Computer Graphics and Computer-Aided Design 10
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Citations per year

Countries citing papers authored by Ryosuke Furuta

Since Specialization
Citations

This map shows the geographic impact of Ryosuke Furuta'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 Ryosuke Furuta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryosuke Furuta more than expected).

Fields of papers citing papers by Ryosuke Furuta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryosuke Furuta. 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 Ryosuke Furuta. The network helps show where Ryosuke Furuta may publish in the future.

Co-authors

The 25 scholars most cited alongside Ryosuke Furuta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Ryosuke Furuta Line = papers co-authored together Ryosuke Furuta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201968
2 201456
3 201931
4 201017
5 201516
6 201712
7 201610
8 202310
9 20239
10
Development of the Fuel Cell Hybrid Railcar
20086
11 20166
12 20195
13
By way of an introduction. Structured documents: what and why?
19894
14 20213
15 20053
16 20213
17 20173
18 20242
19 20212
20 20142

About Ryosuke Furuta

Ryosuke Furuta is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Industrial and Manufacturing Engineering and Mechanical Engineering, having authored 29 papers that have together received 272 indexed citations. Recurring topics across this work include Advanced Vision and Imaging (6 papers), Image Enhancement Techniques (5 papers), Multimodal Machine Learning Applications (4 papers), Human Pose and Action Recognition (4 papers), Advanced Image and Video Retrieval Techniques (4 papers), Video Analysis and Summarization (4 papers), Video Surveillance and Tracking Methods (3 papers) and Electrical Contact Performance and Analysis (3 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (126 citations), Industrial and Manufacturing Engineering (57 citations), Automotive Engineering (52 citations), Health Informatics (4 citations) and Computer Graphics and Computer-Aided Design (10 citations). Ryosuke Furuta has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Toshihiko Yamasaki, Naoto Inoue, Yohei Kono, Hiroshi Yokoyama, Kiyoharu Aizawa, Keiichiro Kondo, Yoichi Sato, Danushka Bollegala, Yusuke Fukushima and Yukinobu Taniguchi. Their work appears in journals such as Multimedia Tools and Applications, International Journal of Computer Vision, Proceedings of the IEEE, IEEE Transactions on Multimedia and IEEE Transactions on Circuits and Systems for Video Technology.

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.

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