Kaoru Arakawa

446 citations
44 papers · 290 · h-index 8

Impact in

Papers in

Kaoru Arakawa

37 papers receiving 267 citations

Peers

Kaoru Arakawa
Comparison fields: 5 of 54
  • Media Technology 86
  • Computer Vision and Pattern Recognition 200
  • Signal Processing 89
  • Pharmacy 22
  • Artificial Intelligence 59
Replace Ryoichi Komiya with:
Ryoichi Komiya Malaysia
S. Gurbuz United States
Bernhard Fröba Germany
K. Sobottka Switzerland
Md. Jahangir Alam Canada
Changbo Hu United States
Abbas Ebrahimi-Moghadam Iran
Abdul Rehman China
Ying Dai Japan
Kaoru Arakawa relative to Ryoichi Komiya Malaysia Ryoichi Komiya's profile →
Citations per field
00.5×3.3×
Ryoichi Komiya · 1×
Citations per year

Countries citing papers authored by Kaoru Arakawa

Since Specialization
Citations

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

Fields of papers citing papers by Kaoru Arakawa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Kaoru Arakawa, 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 Arakawa Line = papers co-authored together Kaoru Arakawa links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 44 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1996116
2 198621
3 200619
4 200615
5 200612
6 201010
7 20099
8 19969
9 19937
10 20127
11 19926
12 20095
13 20105
14
A Digital Image Enlarging Method without Edge Effect by Using the ε-Filter
20034
15 20214
16 20104
17 20083
18 20213
19 19833
20
Optimization of a Piecewise Linear Digital Filter
19872

About Kaoru Arakawa

Kaoru Arakawa is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Social Psychology, Artificial Intelligence and Control and Systems Engineering, having authored 44 papers that have together received 290 indexed citations. Recurring topics across this work include Image and Signal Denoising Methods (10 papers), Color perception and design (7 papers), Music Technology and Sound Studies (7 papers), Speech and Audio Processing (6 papers), Blind Source Separation Techniques (6 papers), Image Enhancement Techniques (5 papers), Neural Networks and Applications (4 papers) and Music and Audio Processing (4 papers). The work is most often cited by research in Media Technology (86 citations), Computer Vision and Pattern Recognition (200 citations), Signal Processing (89 citations), Pharmacy (22 citations) and Artificial Intelligence (59 citations). Kaoru Arakawa has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Hiroshi Harashima, Takuya Okada, Hiroshi Miyakawa, Takashi Matsui, Yasuhiko Arakawa, Derek H. Fender, Noriko Nagata, Keiko Yamashita, Akira Taguchi and Keiko Imamura. Their work appears in journals such as Fuzzy Sets and Systems, International Journal of Imaging Systems and Technology, IEEE Transactions on Biomedical Engineering, The Journal of the Acoustical Society of America and IEICE Transactions on Fundamentals of Electronics Communications and Computer Sciences.

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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