Kaoru Hirota

5.6k citations
295 papers · 4.4k · h-index 31

Impact in

Papers in

Kaoru Hirota

244 papers receiving 4.0k citations

Peers

Kaoru Hirota
Comparison fields: 5 of 149
  • Artificial Intelligence 2.3k
  • Management Science and Operations Research 745
  • Statistics and Probability 455
  • Computational Theory and Mathematics 933
  • Computer Vision and Pattern Recognition 965
Replace Kaoru Hirota with:
Kaoru Hirota Japan
Edwin Lughofer Austria
Fu-Lai Chung Hong Kong
Péter Bárányi Hungary
Alejandro Ribeiro United States
Fábio Gagliardi Cozman Brazil
M. Hanmandlu India
Sridhar Mahadevan United States
Thomas Dean United States
Marc Peter Deisenroth United Kingdom
Kaoru Hirota relative to Kaoru Hirota Japan Kaoru Hirota's profile →
Citations per field
00.5×2.8×
Kaoru Hirota · 1×
Citations per year

Countries citing papers authored by Kaoru Hirota

Since Specialization
Citations

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

Fields of papers citing papers by Kaoru Hirota

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 295 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1993351
2 1997196
3 1981194
4 2019185
5 1993160
6 2009148
7 2019147
8 1999117
9 2018116
10
Industrial Applications of Fuzzy Technology
199387
11 200086
12 200382
13 201276
14 200176
15 200272
16 202269
17 199968
18 200264
19 201964
20 201760

About Kaoru Hirota

Kaoru Hirota is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Computational Theory and Mathematics and Management Science and Operations Research, having authored 295 papers that have together received 4.4k indexed citations. Recurring topics across this work include Fuzzy Logic and Control Systems (93 papers), Neural Networks and Applications (49 papers), Multi-Criteria Decision Making (36 papers), Rough Sets and Fuzzy Logic (32 papers), Image Retrieval and Classification Techniques (24 papers), Fuzzy Systems and Optimization (23 papers), Emotion and Mood Recognition (23 papers) and Face and Expression Recognition (18 papers). The work is most often cited by research in Artificial Intelligence (2.3k citations), Management Science and Operations Research (745 citations), Statistics and Probability (455 citations), Computational Theory and Mathematics (933 citations) and Computer Vision and Pattern Recognition (965 citations). Kaoru Hirota has collaborated with scholars based in Japan, China and Canada. Frequent co-authors include Witold Pedrycz, László T. Kóczy, Jianqiang Yi, N. Yubazaki, Luefeng Chen, Min Wu, Hajime Nobuhara, Fangyan Dong, Joviša Žunić and Paul L. Rosin. Their work appears in journals such as Fuzzy Sets and Systems, Information Sciences, Soft Computing, Applied Soft Computing and IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics).

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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