Atsushi Nakamura

222 papers receiving 1.6k citations

Peers

Atsushi Nakamura
Comparison fields: 5 of 104
  • Artificial Intelligence 955
  • Signal Processing 736
  • Electrical and Electronic Engineering 325
  • Atomic and Molecular Physics, and Optics 259
  • Electronic, Optical and Magnetic Materials 119
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Citations per field
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Citations per year

Countries citing papers authored by Atsushi Nakamura

Since Specialization
Citations

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

Fields of papers citing papers by Atsushi Nakamura

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Atsushi Nakamura

This figure shows the co-authorship network connecting the top 25 collaborators of Atsushi Nakamura. A scholar is included among the top collaborators of Atsushi Nakamura 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 Atsushi Nakamura. Atsushi Nakamura 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 7
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6
Highly sensitive detection of fiber bending using 1-mum-band Mode-detection OTDR
1
7 5
8 1
9
PDN Analysis of LSI Package in Short TAT using TMM and Approximated Equivalent Circuit
1
10
Geometric Margin Control for Minimum Error Classification
1
11
Efficient Discriminative Training of Error Corrective Models Using High-WER Competitors
2
12 3
13
Production-Oriented Models for Speech Recognition(Speech Recognition, Statistical Modeling for Speech Processing)
2
14
Transcatheter arterial embolization for hemorrhage from mesenteric artery pseudoaneurysm caused by seat-belt injury; a case report
4
15 20
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A Study on Measurement of LSI Immunity for PCB Analysis
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17 1
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A study on strength of steel square tubular columns filled with high strength concrete under biaxial eccentric load
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19
Databases for Conversational Speech Translation Research at ATR( Trends in Database for Phonetic Research)
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20 4

About Atsushi Nakamura

Atsushi Nakamura is a scholar working on Signal Processing, Artificial Intelligence and Condensed Matter Physics, having authored 244 papers that have together received 1.7k indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (84 papers), Speech and Audio Processing (60 papers) and Music and Audio Processing (40 papers). The work is most often cited by research in Signal Processing (736 citations), Artificial Intelligence (955 citations) and Atomic and Molecular Physics, and Optics (259 citations). Atsushi Nakamura has collaborated with scholars based in Japan, United States and Germany. Frequent co-authors include Takaaki Hori, Shinji Watanabe, Yasuhiro Minami, Erik McDermott, Shigeru Katagiri, Atsunori Ogawa, Chiori Hori, Timothy J. Hazen, Jonathan Le Roux and Takanobu Oba. Their work appears in journals such as Applied Physics Letters, Journal of Applied Physics and Acta Materialia.

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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