Hidetaka Nambo
- Artificial Intelligence
- Molecular Biology
- Plant Science
- Computer Vision and Pattern Recognition
- Biomedical Engineering
- Co-authors
- Haruhiko KimuraMitsuhiro KometaniTakashi OyabuTakashi YonedaShigehiro KarashimaMasashi DemuraSatoshi NagaseAkinori Hara
- Topics
- Plant and Biological Electrophysiology Studies (7 papers)Advanced Chemical Sensor Technologies (7 papers)Smart Agriculture and AI (4 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- JapanIndonesiaUnited States
In The Last Decade
Hidetaka Nambo
58 papers receiving 171 citations
Peers
Comparison fields: 5 of 98
- Artificial Intelligence 39
- Molecular Biology 29
- Plant Science 21
- Computer Vision and Pattern Recognition 20
- Biomedical Engineering 19
Countries citing papers authored by Hidetaka Nambo
This map shows the geographic impact of Hidetaka Nambo'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 Hidetaka Nambo with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Hidetaka Nambo more than expected).
Fields of papers citing papers by Hidetaka Nambo
This network shows the impact of papers produced by Hidetaka Nambo. 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 Hidetaka Nambo. The network helps show where Hidetaka Nambo may publish in the future.
Co-authorship network of co-authors of Hidetaka Nambo
This figure shows the co-authorship network connecting the top 25 collaborators of Hidetaka Nambo. A scholar is included among the top collaborators of Hidetaka Nambo 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 Hidetaka Nambo. Hidetaka Nambo is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 3 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 10 | |
| 10 | 2 | |
| 11 | 11 | |
| 12 | 11 | |
| 13 | 5 | |
| 14 | Time Complexity Of A Priori And Evolutionary Algorithm For Numerical Association Rule Mining Optimization | 2 |
| 15 | Estimating Position of Bio-Electric Potential Dataset as A Natural Sensor using Time Series Approach. | 2 |
| 16 | 0 | |
| 17 | 1 | |
| 18 | Metrical Linguistic Analysis of English Materials for Tourism | 2 |
| 19 | Relative Difficulty of Various English Writings by Fuzzy Reasoning and Its Application to Selecting Teaching Materials | 6 |
| 20 | 1 |
About Hidetaka Nambo
Hidetaka Nambo is a scholar working on Tourism, Leisure and Hospitality Management, Artificial Intelligence and Information Systems, having authored 68 papers that have together received 184 indexed citations. Recurring topics across this work include Plant and Biological Electrophysiology Studies (7 papers), Advanced Chemical Sensor Technologies (7 papers) and Smart Agriculture and AI (4 papers). The work is most often cited by research in Health Informatics (5 citations), Nephrology (17 citations) and Artificial Intelligence (39 citations). Hidetaka Nambo has collaborated with scholars based in Japan, Indonesia and United States. Frequent co-authors include Haruhiko Kimura, Mitsuhiro Kometani, Takashi Oyabu, Takashi Yoneda, Shigehiro Karashima, Masashi Demura, Satoshi Nagase, Akinori Hara, Hiromasa Tsujiguchi and Kenji Furukawa. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.