K. Maeda

1.3k citations
74 papers · 964 · h-index 14

Impact in

Papers in

K. Maeda

71 papers receiving 776 citations

Peers

K. Maeda
Comparison fields: 5 of 82
  • Astronomy and Astrophysics 433
  • Computer Vision and Pattern Recognition 337
  • Geophysics 166
  • Signal Processing 69
  • Media Technology 51
Replace J. F. Jarvis with:
J. F. Jarvis United States
J. A. Högbom Australia
Katherine L. Bouman United States
E. Chassande‐Mottin France
W. Macy United States
Gerald Kaiser United States
Bernhard Wirnitzer Germany
Ajit Kembhavi India
J.W. Haslett Canada
Sofia Suvorova Australia
K. Maeda relative to J. F. Jarvis United States J. F. Jarvis's profile →
Citations per field
00.5×9.8×
J. F. Jarvis · 1×
Citations per year

Countries citing papers authored by K. Maeda

Since Specialization
Citations

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

Fields of papers citing papers by K. Maeda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 74 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002316
2 196659
3 196659
4 196353
5 197141
6 196939
7 197732
8 195927
9 200422
10 196321
11 200219
12 195217
13 200116
14
IONOSPHERIC DYNAMO THEORY WITH CONSIDERATION FOR MAGNETOSPHERIC CURRENT ALONG THE GEOMAGNETIC LINES OF FORCE
196515
15 195413
16 200513
17
Identifying Cellular Automata Rules
200711
18 196810
19
From the Subspace Methods to the Mutual Subspace Method.
20109
20 19657

About K. Maeda

K. Maeda is a scholar working on Astronomy and Astrophysics, Electrical and Electronic Engineering, Aerospace Engineering, Molecular Biology and Computer Vision and Pattern Recognition, having authored 74 papers that have together received 964 indexed citations. Recurring topics across this work include Ionosphere and magnetosphere dynamics (25 papers), Solar and Space Plasma Dynamics (20 papers), Geomagnetism and Paleomagnetism Studies (10 papers), Radio Frequency Integrated Circuit Design (8 papers), GNSS positioning and interference (7 papers), Earthquake Detection and Analysis (5 papers), Geophysics and Gravity Measurements (4 papers) and Plasma Diagnostics and Applications (4 papers). The work is most often cited by research in Astronomy and Astrophysics (433 citations), Computer Vision and Pattern Recognition (337 citations), Geophysics (166 citations), Signal Processing (69 citations) and Media Technology (51 citations). K. Maeda has collaborated with scholars based in Japan, United States and Brazil. Frequent co-authors include Osamu Yamaguchi, Eriko Fukui, S. Kato, Takao Tsuda, Tetsuya Sato, Toshitaka Tsuda, Hajime Maeda, T. Sato, Hiroshi Oya and M. Wada. Their work appears in journals such as Journal of geomagnetism and geoelectricity, IEICE Transactions on Electronics, Radio Science, Planetary and Space Science and Langmuir.

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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