Noboru Koshizuka
- Human-Computer Interaction top 5%
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- IoT and Edge/Fog Computing 11
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- Context-Aware Activity Recognition Systems 24
- Information Systems top 5%
- Building and Construction top 5%
- Smart Parking Systems Research 13
- Traffic Prediction and Management Techniques 9
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- Indoor and Outdoor Localization Technologies 16
- Ultra-Wideband Communications Technology 8
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- Human Mobility and Location-Based Analysis 13
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- Privacy-Preserving Technologies in Data 8
Noboru Koshizuka
105 papers receiving 985 citations
Peers
Comparison fields: 5 of 92
- Human-Computer Interaction 74
- Computer Networks and Communications 268
- Computer Vision and Pattern Recognition 200
- Information Systems 210
- Building and Construction 103
Countries citing papers authored by Noboru Koshizuka
This map shows the geographic impact of Noboru Koshizuka'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 Noboru Koshizuka with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Noboru Koshizuka more than expected).
Fields of papers citing papers by Noboru Koshizuka
This network shows the impact of papers produced by Noboru Koshizuka. 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 Noboru Koshizuka. The network helps show where Noboru Koshizuka may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Noboru Koshizuka, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 2 | |
| 2 | 2025 | 5 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 0 | |
| 5 | 2023 | 2 | |
| 6 | 2022 | 5 | |
| 7 | 2022 | 0 | |
| 8 | 2020 | 4 | |
| 9 | 2020 | 3 | |
| 10 | 2019 | 9 | |
| 11 | 2015 | 4 | |
| 12 | Near drowning pattern recognition using neural network and wearable pressure and inertial sensors attached at swimmer's chest level | 2012 | 3 |
| 13 | 2012 | 2 | |
| 14 | ucR-based spatial information framework | 2011 | 1 |
| 15 | 2011 | 1 | |
| 16 | 2010 | 3 | |
| 17 | 2008 | 1 | |
| 18 | 2007 | 6 | |
| 19 | 2004 | 1 | |
| 20 | Large-scale Ubiquitous Information System for Digital Museum. | 2003 | 5 |
About Noboru Koshizuka
Noboru Koshizuka is a scholar working on Human-Computer Interaction, Transportation and Building and Construction, having authored 123 papers that have together received 1.0k indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (24 papers), Indoor and Outdoor Localization Technologies (16 papers), Human Mobility and Location-Based Analysis (13 papers), Smart Parking Systems Research (13 papers), IoT and Edge/Fog Computing (11 papers), Traffic Prediction and Management Techniques (9 papers), Ultra-Wideband Communications Technology (8 papers) and Privacy-Preserving Technologies in Data (8 papers). The work is most often cited by research in Human-Computer Interaction (74 citations), Computer Networks and Communications (268 citations) and Computer Vision and Pattern Recognition (200 citations). Noboru Koshizuka has collaborated with scholars based in Japan, China and Australia. Frequent co-authors include Ken Sakamura, Shinsuke Kobayashi, Jee‐Eun Kim, M. Miyazaki, Takeo Hamada, Masaru Kokubo, Yousuke Ogata, Tatsuo Nakagawa, Jong-Moon Choi and Xiaohui Peng. Their work appears in journals such as IEEE Access, IEEE Journal of Solid-State Circuits and Computer.
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.