Toru Imai

1.3k citations
80 papers · 745 · h-index 12

Impact in

Papers in

Toru Imai

65 papers receiving 635 citations

Peers

Toru Imai
Comparison fields: 5 of 90
  • Software 99
  • Signal Processing 89
  • Nuclear and High Energy Physics 95
  • Information Systems 153
  • Artificial Intelligence 198
Replace Hyun‐Su Kim with:
Hyun‐Su Kim South Korea
Lieven Desmet Belgium
N. Seifert United States
V.K. Agarwal Canada
Lijun Cai China
J.B. Bernstein United States
A. Visconti Italy
Zhiwei Shi China
Matthias Neubauer Austria
Manish Prasad United States
Toru Imai relative to Hyun‐Su Kim South Korea Hyun‐Su Kim's profile →
Citations per field
00.5×10×16.5×
Hyun‐Su Kim · 1×
Citations per year

Countries citing papers authored by Toru Imai

Since Specialization
Citations

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

Fields of papers citing papers by Toru Imai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Toru Imai, 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 Toru Imai Line = papers co-authored together Toru Imai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 80 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006189
2 2003134
3 200548
4 199740
5 200529
6 200022
7 200322
8 200221
9 200618
10 200812
11 200212
12 201911
13 200211
14 200310
15 199810
16 20239
17 20079
18 20028
19 20138
20 20138

About Toru Imai

Toru Imai is a scholar working on Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition, Nuclear and High Energy Physics and Astronomy and Astrophysics, having authored 80 papers that have together received 745 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (25 papers), Speech and Audio Processing (15 papers), Magnetic confinement fusion research (13 papers), Ionosphere and magnetosphere dynamics (10 papers), Subtitles and Audiovisual Media (10 papers), Natural Language Processing Techniques (9 papers), Music and Audio Processing (6 papers) and Advanced Data Compression Techniques (5 papers). The work is most often cited by research in Software (99 citations), Signal Processing (89 citations), Nuclear and High Energy Physics (95 citations), Information Systems (153 citations) and Artificial Intelligence (198 citations). Toru Imai has collaborated with scholars based in Japan, South Korea and United States. Frequent co-authors include Toshikatsu Tanaka, Toshio Shimizu, T. Ozaki, Fumio Sawa, Masahiro Kozako, Takashi Nakano, Akio Kobayashi, Francis Kubala, A Ando and Akio Ando. Their work appears in journals such as Fusion Science & Technology, Nuclear Fusion, IEEE Transactions on Broadcasting, Cytometry Part A and Japanese Journal of Clinical Oncology.

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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