S. Matsunaga

456 citations
31 papers · 292 indexed · h-index 10
Topics
Speech Recognition and Synthesis (15 papers)Natural Language Processing Techniques (8 papers)Speech and Audio Processing (7 papers)
Partner nations
JapanChileUnited Kingdom

In The Last Decade

S. Matsunaga

29 papers receiving 258 citations

Peers

S. Matsunaga
Comparison fields: 5 of 71
  • Artificial Intelligence 127
  • Signal Processing 79
  • Surgery 54
  • Pathology and Forensic Medicine 48
  • Nutrition and Dietetics 44
Replace Ashish Kapoor with:
Ashish Kapoor United States
Pooja Sharma India
Heidi Gregersen Denmark
Jonas Ghouse Denmark
Sibaji Gaj India
Annaliisa Kankainen Finland
Mihir Shah United States
Abdelrahman Mohamed United States
Jordi Huguet Spain
Jianye Zhang China
S. Matsunaga relative to Ashish Kapoor United States Ashish Kapoor's profile →
Citations per field
00.5×7.2×
Ashish Kapoor · 1×
Citations per year

Countries citing papers authored by S. Matsunaga

Since Specialization
Citations

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

Fields of papers citing papers by S. Matsunaga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of S. Matsunaga

This figure shows the co-authorship network connecting the top 25 collaborators of S. Matsunaga. A scholar is included among the top collaborators of S. Matsunaga 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 S. Matsunaga. S. Matsunaga 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 1
2 1
3 2
4 10
5 7
6 9
7 2
8 26
9 5
10 0
11 3
12 3
13 53
14 52
15
Retinoid and bone metabolic marker in ossification of the posterior longitudinal ligament.
14
16 5
17 1
18 0
19 2
20 1

About S. Matsunaga

S. Matsunaga is a scholar working on Signal Processing, Pharmacy and Artificial Intelligence, having authored 31 papers that have together received 292 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (15 papers), Natural Language Processing Techniques (8 papers) and Speech and Audio Processing (7 papers). The work is most often cited by research in Signal Processing (79 citations), Artificial Intelligence (127 citations) and Nutrition and Dietetics (44 citations). S. Matsunaga has collaborated with scholars based in Japan, Chile and United Kingdom. Frequent co-authors include Takashi Sakou, Hiroshi Ito, T. Shimizu, Yoshinori Sagisaka, Kiyohiro Shikano, Tatsuro Yamada, Katsunori Ikari, Hiroaki Koga, Hirokazu Masataki and Takuya Numasawa. Their work appears in journals such as IEEE Signal Processing Magazine, Calcified Tissue International and Electronics Letters.

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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