Masaki Samejima

528 citations
59 papers · 377 · h-index 9

Impact in

Papers in

Masaki Samejima

45 papers receiving 357 citations

Peers

Masaki Samejima
Comparison fields: 5 of 96
  • Computer Graphics and Computer-Aided Design 100
  • Computer Vision and Pattern Recognition 152
  • Developmental Biology 10
  • Geology 21
  • Information Systems 68
Replace Youngmin Kim with:
Youngmin Kim South Korea
Michael Cox United States
Kang Zhang China
Jinyuan Jia China
Qiang Lü China
Marc Benkert Germany
Long Peng China
Damjan Strnad Slovenia
Nivan Ferreira Brazil
Chén Mĭn United States
Masaki Samejima relative to Youngmin Kim South Korea Youngmin Kim's profile →
Citations per field
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Citations per year

Countries citing papers authored by Masaki Samejima

Since Specialization
Citations

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

Fields of papers citing papers by Masaki Samejima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 22 scholars most cited alongside Masaki Samejima, 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 Masaki Samejima Line = papers co-authored together Masaki Samejima links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 59 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017114
2 202036
3 201726
4 200626
5 202020
6 201319
7 201717
8 20148
9 20128
10 20157
11 20127
12 20117
13 20147
14 20086
15 20135
16 20184
17 20134
18 20154
19 20093
20 20173

About Masaki Samejima

Masaki Samejima is a scholar working on Information Systems, Artificial Intelligence, Computer Networks and Communications, Management Information Systems and Management Science and Operations Research, having authored 59 papers that have together received 377 indexed citations. Recurring topics across this work include Advanced Text Analysis Techniques (8 papers), Supply Chain and Inventory Management (5 papers), Web Data Mining and Analysis (5 papers), Cloud Computing and Resource Management (5 papers), Semantic Web and Ontologies (5 papers), Multi-Criteria Decision Making (5 papers), Network Security and Intrusion Detection (5 papers) and Supply Chain Resilience and Risk Management (5 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (100 citations), Computer Vision and Pattern Recognition (152 citations), Developmental Biology (10 citations), Geology (21 citations) and Information Systems (68 citations). Masaki Samejima has collaborated with scholars based in Japan, Finland and China. Frequent co-authors include Yasuyuki Matsushita, Yusuke Sugano, Norihisa Komoda, Boxin Shi, Ryôichi Sasaki, Yutaka Shimizu, Junichi Nakai, Asako Kanezaki, Hiroshi Yajima and Takuya Maekawa. Their work appears in journals such as Information Systems, Interactive Technology and Smart Education, European Journal of Operational Research, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Systems Man and Cybernetics Systems.

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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