Akiko Nakashima
- Electrical and Electronic Engineering top 10%
- Electronic, Optical and Magnetic Materials
- Automotive Engineering top 10%
- Mechanical Engineering
- Materials Chemistry
- Co-authors
- Mitsuharu TabuchiHiroyuki KageyamaKuniaki TatsumiKazuaki AdoHikarí SakaebeH. KobayashiTatsuya NakamuraRyoji Kanno
- Topics
- Advancements in Battery Materials (8 papers)Advanced Battery Materials and Technologies (6 papers)Neural Networks and Applications (4 papers)
- Cited by
- Electronic, Optical and Magnetic MaterialsAutomotive EngineeringElectrical and Electronic Engineering
- Partner nations
- JapanUnited KingdomSwitzerland
In The Last Decade
Akiko Nakashima
17 papers receiving 379 citations
Peers
Comparison fields: 5 of 46
- Electrical and Electronic Engineering 323
- Electronic, Optical and Magnetic Materials 147
- Automotive Engineering 87
- Mechanical Engineering 87
- Materials Chemistry 53
Countries citing papers authored by Akiko Nakashima
This map shows the geographic impact of Akiko Nakashima'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 Akiko Nakashima with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akiko Nakashima more than expected).
Fields of papers citing papers by Akiko Nakashima
This network shows the impact of papers produced by Akiko Nakashima. 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 Akiko Nakashima. The network helps show where Akiko Nakashima may publish in the future.
Co-authorship network of co-authors of Akiko Nakashima
This figure shows the co-authorship network connecting the top 25 collaborators of Akiko Nakashima. A scholar is included among the top collaborators of Akiko Nakashima 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 Akiko Nakashima. Akiko Nakashima is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 9 | |
| 3 | Head Pose Estimation using Adaptively Scaled Template Matching. | 3 |
| 4 | 38 | |
| 5 | 41 | |
| 6 | 9 | |
| 7 | 34 | |
| 8 | 20 | |
| 9 | 35 | |
| 10 | 7 | |
| 11 | 75 | |
| 12 | 3 | |
| 13 | 86 | |
| 14 | 0 | |
| 15 | 9 | |
| 16 | 2 | |
| 17 | 10 | |
| 18 | 4 |
About Akiko Nakashima
Akiko Nakashima is a scholar working on Computer Vision and Pattern Recognition, Signal Processing and Human-Computer Interaction, having authored 18 papers that have together received 386 indexed citations. Recurring topics across this work include Advancements in Battery Materials (8 papers), Advanced Battery Materials and Technologies (6 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Electronic, Optical and Magnetic Materials (147 citations), Automotive Engineering (87 citations) and Electrical and Electronic Engineering (323 citations). Akiko Nakashima has collaborated with scholars based in Japan, United Kingdom and Switzerland. Frequent co-authors include Mitsuharu Tabuchi, Hiroyuki Kageyama, Kuniaki Tatsumi, Kazuaki Ado, Hikarí Sakaebe, H. Kobayashi, Tatsuya Nakamura, Ryoji Kanno, Hikari Shigemura and Atsushi Hirano. Their work appears in journals such as Chemistry of Materials, Journal of The Electrochemical Society and Journal of Power Sources.
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.