Jun Kitazono
Impact in
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- Neural dynamics and brain function
- Functional Brain Connectivity Studies
- Face Recognition and Perception
- Visual perception and processing mechanisms
- EEG and Brain-Computer Interfaces
Papers in
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- Neural dynamics and brain function 8
- Functional Brain Connectivity Studies 7
- EEG and Brain-Computer Interfaces 3
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- Internet Traffic Analysis and Secure E-voting 3
- Sentiment Analysis and Opinion Mining 3
- Co-authors
- Seiichi Ozawa (11 shared papers)Masato Okada (4 shared papers)Toshiaki Omori (5 shared papers)Masafumi Oizumi (8 shared papers)Takayuki Sato (1 shared paper)Manabu Tanifuji (1 shared paper)Mark D. Lescroart (1 shared paper)Kenji Nagata (2 shared papers)
In The Last Decade
Jun Kitazono
23 papers receiving 264 citations
Peers
Comparison fields: 5 of 73
- Cognitive Neuroscience 98
- Artificial Intelligence 86
- Signal Processing 26
- Computer Networks and Communications 41
- Computational Mathematics 1
Countries citing papers authored by Jun Kitazono
This map shows the geographic impact of Jun Kitazono'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 Jun Kitazono with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Kitazono more than expected).
Fields of papers citing papers by Jun Kitazono
This network shows the impact of papers produced by Jun Kitazono. 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 Jun Kitazono. The network helps show where Jun Kitazono may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Kitazono, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 43 | |
| 2 | 2014 | 38 | |
| 3 | 2017 | 37 | |
| 4 | 2014 | 24 | |
| 5 | 2017 | 21 | |
| 6 | 2015 | 20 | |
| 7 | 2014 | 18 | |
| 8 | 2020 | 14 | |
| 9 | 2016 | 11 | |
| 10 | 2015 | 10 | |
| 11 | 2022 | 9 | |
| 12 | 2012 | 4 | |
| 13 | 2021 | 4 | |
| 14 | 2015 | 4 | |
| 15 | 2022 | 4 | |
| 16 | 2016 | 4 | |
| 17 | 2016 | 2 | |
| 18 | 2009 | 2 | |
| 19 | 2016 | 2 | |
| 20 | 2017 | 1 |
About Jun Kitazono
Jun Kitazono is a scholar working on Cognitive Neuroscience, Artificial Intelligence, Signal Processing, Computer Vision and Pattern Recognition and Electrochemistry, having authored 24 papers that have together received 275 indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Functional Brain Connectivity Studies (7 papers), Network Security and Intrusion Detection (4 papers), EEG and Brain-Computer Interfaces (3 papers), Internet Traffic Analysis and Secure E-voting (3 papers), Face and Expression Recognition (3 papers), Spam and Phishing Detection (3 papers) and Sentiment Analysis and Opinion Mining (3 papers). The work is most often cited by research in Cognitive Neuroscience (98 citations), Artificial Intelligence (86 citations), Signal Processing (26 citations), Computer Networks and Communications (41 citations) and Computational Mathematics (1 citation). Jun Kitazono has collaborated with scholars based in Japan, France and Denmark. Frequent co-authors include Seiichi Ozawa, Masato Okada, Toshiaki Omori, Masafumi Oizumi, Takayuki Sato, Manabu Tanifuji, Mark D. Lescroart, Kenji Nagata, Tao Ban and Nistor Grozavu. Their work appears in journals such as Journal of Neuroscience, Brain stimulation, Cerebral Cortex, Frontiers in Human Neuroscience and Cell 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.