Wenxuan Mou
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- Face recognition and analysis 6
- Human Pose and Action Recognition 5
- Cognitive Neuroscience top 10%
- Tactile and Sensory Interactions 3
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- Emotion and Mood Recognition 5
- Human-Computer Interaction top 10%
- Signal Processing top 10%
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- Advanced Sensor and Energy Harvesting Materials 3
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- Social Robot Interaction and HRI 3
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- Anomaly Detection Techniques and Applications 2
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- Robot Manipulation and Learning 2
- Co-authors
- Hatice GüneşKaspar AlthoeferShan LuoHongbin LiuIoannis PatrasOya ÇeliktutanToshiaki Koike‐AkinoTim K. Marks
- Cited by
- Computer Vision and Pattern RecognitionCognitive NeuroscienceExperimental and Cognitive Psychology
- Journals
- IEEE Sensors Journal (1 paper)Image and Vision Computing (1 paper)Autonomous Robots (1 paper)
- Partner nations
- United KingdomGreeceJapan
In The Last Decade
Wenxuan Mou
15 papers receiving 379 citations
Peers
Comparison fields: 5 of 57
- Computer Vision and Pattern Recognition 185
- Cognitive Neuroscience 121
- Experimental and Cognitive Psychology 71
- Human-Computer Interaction 26
- Signal Processing 44
Countries citing papers authored by Wenxuan Mou
This map shows the geographic impact of Wenxuan Mou'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 Wenxuan Mou with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wenxuan Mou more than expected).
Fields of papers citing papers by Wenxuan Mou
This network shows the impact of papers produced by Wenxuan Mou. 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 Wenxuan Mou. The network helps show where Wenxuan Mou may publish in the future.
Co-authorship network
The 23 scholars most cited alongside Wenxuan Mou, 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 | 2021 | 12 | |
| 2 | 2020 | 87 | |
| 3 | 2020 | 29 | |
| 4 | 2019 | 2 | |
| 5 | 2019 | 13 | |
| 6 | 2019 | 8 | |
| 7 | 2018 | 25 | |
| 8 | 2018 | 2 | |
| 9 | 2017 | 1 | |
| 10 | 2016 | 19 | |
| 11 | 2016 | 16 | |
| 12 | 2015 | 39 | |
| 13 | 2015 | 78 | |
| 14 | 2015 | 37 | |
| 15 | 2014 | 17 |
About Wenxuan Mou
Wenxuan Mou is a scholar working on Computer Vision and Pattern Recognition, Experimental and Cognitive Psychology and Cognitive Neuroscience, having authored 15 papers that have together received 385 indexed citations. Recurring topics across this work include Face recognition and analysis (6 papers), Emotion and Mood Recognition (5 papers), Human Pose and Action Recognition (5 papers), Tactile and Sensory Interactions (3 papers), Advanced Sensor and Energy Harvesting Materials (3 papers), Social Robot Interaction and HRI (3 papers), Anomaly Detection Techniques and Applications (2 papers) and Robot Manipulation and Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (185 citations), Cognitive Neuroscience (121 citations) and Experimental and Cognitive Psychology (71 citations). Wenxuan Mou has collaborated with scholars based in United Kingdom, Greece and Japan. Frequent co-authors include Hatice Güneş, Kaspar Althoefer, Shan Luo, Hongbin Liu, Ioannis Patras, Oya Çeliktutan, Toshiaki Koike‐Akino, Tim K. Marks, Anoop Cherian and Angelo Cangelosi. Their work appears in journals such as IEEE Sensors Journal, Image and Vision Computing and Autonomous Robots.
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.