Rintaro Ikeshita

708 citations
53 papers · 436 indexed · h-index 12
Topics
Speech and Audio Processing (45 papers)Blind Source Separation Techniques (31 papers)Advanced Adaptive Filtering Techniques (28 papers)
Partner nations
JapanUnited StatesFrance

In The Last Decade

Rintaro Ikeshita

45 papers receiving 401 citations

Peers

Rintaro Ikeshita
Comparison fields: 5 of 29
  • Signal Processing 414
  • Computational Mechanics 200
  • Artificial Intelligence 159
  • Cognitive Neuroscience 38
  • Computer Vision and Pattern Recognition 14
Replace Norihiro Takamune with:
Norihiro Takamune Japan
Ngoc Q. K. Duong France
Antti Hurmalainen Finland
Tomoya Takatani Japan
Aditya Arie Nugraha Japan
Radoslaw Mazur Germany
A. Lee Japan
Kouhei Sekiguchi Japan
Robin Scheibler Japan
Rasmus Kongsgaard Olsson Denmark
Rintaro Ikeshita relative to Norihiro Takamune Japan Norihiro Takamune's profile →
Citations per field
00.5×2.9×
Norihiro Takamune · 1×
Citations per year

Countries citing papers authored by Rintaro Ikeshita

Since Specialization
Citations

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

Fields of papers citing papers by Rintaro Ikeshita

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rintaro Ikeshita

This figure shows the co-authorship network connecting the top 25 collaborators of Rintaro Ikeshita. A scholar is included among the top collaborators of Rintaro Ikeshita 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 Rintaro Ikeshita. Rintaro Ikeshita is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 5
3 0
4 4
5 2
6 4
7 1
8 0
9 3
10 0
11 16
12 18
13 2
14 15
15 52
16 14
17 1
18 2
19 2
20 2

About Rintaro Ikeshita

Rintaro Ikeshita is a scholar working on Signal Processing, Computational Mathematics and Computational Mechanics, having authored 53 papers that have together received 436 indexed citations. Recurring topics across this work include Speech and Audio Processing (45 papers), Blind Source Separation Techniques (31 papers) and Advanced Adaptive Filtering Techniques (28 papers). The work is most often cited by research in Signal Processing (414 citations), Computational Mechanics (200 citations) and Computational Mathematics (5 citations). Rintaro Ikeshita has collaborated with scholars based in Japan, United States and France. Frequent co-authors include Tomohiro Nakatani, Shoko Araki, Keisuke Kinoshita, Hiroshi Sawada, Marc Delcroix, Tsubasa Ochiai, Nobutaka Ito, Naoyuki Kamo, Yohei Kawaguchi and Yusuke Fujita. Their work appears in journals such as IEEE Transactions on Signal Processing, IEEE Signal Processing Letters and Computer Speech & Language.

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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