Senya Polikovsky
Impact in
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- Emotion and Mood Recognition
- Human-Computer Interaction top 5%
- Hand Gesture Recognition Systems
- Gaze Tracking and Assistive Technology
Papers in
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- Human Pose and Action Recognition 4
- Face recognition and analysis 2
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- Emotion and Mood Recognition 4
- Co-authors
- Yoshinari Kameda (4 shared papers)Yuichi Ohta (4 shared papers)Hongwei Yi (1 shared paper)Daniel Scharstein (1 shared paper)Michael J. Black (2 shared papers)Chun-Hao P. Huang (1 shared paper)Egidio Ragonese (2 shared papers)Concetto Spampinato (1 shared paper)
- Journals
- Scientific Data (1 paper)IEICE Transactions on Information and Systems (1 paper)Lecture notes in computer science (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (1 paper)MPG.PuRe (Max Planck Society) (1 paper)
In The Last Decade
Senya Polikovsky
10 papers receiving 407 citations
Peers
Comparison fields: 5 of 43
- Experimental and Cognitive Psychology 221
- Human-Computer Interaction 95
- Computer Vision and Pattern Recognition 290
- Urban Studies 34
- Signal Processing 41
Countries citing papers authored by Senya Polikovsky
This map shows the geographic impact of Senya Polikovsky'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 Senya Polikovsky with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Senya Polikovsky more than expected).
Fields of papers citing papers by Senya Polikovsky
This network shows the impact of papers produced by Senya Polikovsky. 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 Senya Polikovsky. The network helps show where Senya Polikovsky may publish in the future.
Co-authors
The 18 scholars most cited alongside Senya Polikovsky, 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 | 2009 | 242 | |
| 2 | 2022 | 79 | |
| 3 | 2012 | 57 | |
| 4 | Detection and measurement of facial micro-expression characteristics for psychological analysis (ヒューマン情報処理) | 2010 | 12 |
| 5 | 2025 | 8 | |
| 6 | 2025 | 7 | |
| 7 | 2024 | 4 | |
| 8 | 2024 | 4 | |
| 9 | 2012 | 4 | |
| 10 | 2012 | 1 |
About Senya Polikovsky
Senya Polikovsky is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology, Human-Computer Interaction, Artificial Intelligence and Social Psychology, having authored 10 papers that have together received 418 indexed citations. Recurring topics across this work include Human Pose and Action Recognition (4 papers), Emotion and Mood Recognition (4 papers), Hand Gesture Recognition Systems (3 papers), Anomaly Detection Techniques and Applications (2 papers), Face recognition and analysis (2 papers), Color perception and design (1 paper), Human Motion and Animation (1 paper) and Hearing Impairment and Communication (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (221 citations), Human-Computer Interaction (95 citations), Computer Vision and Pattern Recognition (290 citations), Urban Studies (34 citations) and Signal Processing (41 citations). Senya Polikovsky has collaborated with scholars based in Japan, Germany and Italy. Frequent co-authors include Yoshinari Kameda, Yuichi Ohta, Hongwei Yi, Daniel Scharstein, Michael J. Black, Chun-Hao P. Huang, Egidio Ragonese, Concetto Spampinato, Silvia Zuffi and Isaak Kavasidis. Their work appears in journals such as Scientific Data, IEICE Transactions on Information and Systems, Lecture notes in computer science, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and MPG.PuRe (Max Planck Society).
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.