Mark Elshaw
Impact in
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- Emotion and Mood Recognition
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- Face and Expression Recognition
- Face recognition and analysis
Papers in
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- Action Observation and Synchronization 13
- Social Robot Interaction and HRI 5
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- Neural dynamics and brain function 7
- Co-authors
- Stefan Wermter (23 shared papers)Vasile Palade (8 shared papers)Cornelius Weber (13 shared papers)Günther Palm (4 shared papers)M. Nazmul Huda (2 shared papers)Sujan Rajbhandari (2 shared papers)Stratis Kanarachos (2 shared papers)Chitta Saha (2 shared papers)
- Journals
- Neural Networks (2 papers)Connection Science (2 papers)Knowledge-Based Systems (1 paper)Sensors and Actuators A Physical (1 paper)Neural Computing and Applications (1 paper)
- Partner nations
- United KingdomGermanyItaly
In The Last Decade
Mark Elshaw
37 papers receiving 493 citations
Peers
Comparison fields: 5 of 93
- Experimental and Cognitive Psychology 149
- Computer Vision and Pattern Recognition 204
- Cognitive Neuroscience 123
- Social Psychology 129
- Human-Computer Interaction 27
Countries citing papers authored by Mark Elshaw
This map shows the geographic impact of Mark Elshaw'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 Mark Elshaw with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Elshaw more than expected).
Fields of papers citing papers by Mark Elshaw
This network shows the impact of papers produced by Mark Elshaw. 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 Mark Elshaw. The network helps show where Mark Elshaw may publish in the future.
Co-authors
The 23 scholars most cited alongside Mark Elshaw, 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 37 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 71 | |
| 2 | 2018 | 64 | |
| 3 | 2005 | 48 | |
| 4 | 2017 | 42 | |
| 5 | 2004 | 35 | |
| 6 | 2016 | 28 | |
| 7 | 2013 | 20 | |
| 8 | 1999 | 20 | |
| 9 | 2018 | 18 | |
| 10 | 2005 | 16 | |
| 11 | 2003 | 16 | |
| 12 | Biomimetic Neural Learning for Intelligent Robots: Intelligent Systems, Cognitive Robotics, and Neuroscience | 2005 | 16 |
| 13 | 2020 | 14 | |
| 14 | 2006 | 9 | |
| 15 | 2005 | 9 | |
| 16 | 2018 | 8 | |
| 17 | 2008 | 8 | |
| 18 | 2001 | 8 | |
| 19 | 2003 | 7 | |
| 20 | 2005 | 7 |
About Mark Elshaw
Mark Elshaw is a scholar working on Social Psychology, Cognitive Neuroscience, Control and Systems Engineering, Computer Vision and Pattern Recognition and Experimental and Cognitive Psychology, having authored 37 papers that have together received 521 indexed citations. Recurring topics across this work include Action Observation and Synchronization (13 papers), Robot Manipulation and Learning (11 papers), Emotion and Mood Recognition (8 papers), Neural dynamics and brain function (7 papers), Face recognition and analysis (6 papers), Face and Expression Recognition (5 papers), Social Robot Interaction and HRI (5 papers) and Neural Networks and Applications (4 papers). The work is most often cited by research in Experimental and Cognitive Psychology (149 citations), Computer Vision and Pattern Recognition (204 citations), Cognitive Neuroscience (123 citations), Social Psychology (129 citations) and Human-Computer Interaction (27 citations). Mark Elshaw has collaborated with scholars based in United Kingdom, Germany and Italy. Frequent co-authors include Stefan Wermter, Vasile Palade, Cornelius Weber, Günther Palm, M. Nazmul Huda, Sujan Rajbhandari, Stratis Kanarachos, Chitta Saha, Friedemann Pulvermüller and Christo Panchev. Their work appears in journals such as Neural Networks, Connection Science, Knowledge-Based Systems, Sensors and Actuators A Physical and Neural Computing and Applications.
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.