Michèle Fabre‐Thorpe
- Cognitive Neuroscience top 0.5%
- Computer Vision and Pattern Recognition top 1%
- Experimental and Cognitive Psychology top 2%
- Social Psychology top 5%
- Sensory Systems top 2%
- Co-authors
- Simon J. ThorpeGuillaume A. RousseletMarc J.‐M. MacéO. JoubertArnaud DelormeDenis FizeGhislaine RichardNadège Bacon-Macé
- Topics
- Face Recognition and Perception (29 papers)Visual perception and processing mechanisms (20 papers)Neural dynamics and brain function (16 papers)
In The Last Decade
Michèle Fabre‐Thorpe
41 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 111
- Cognitive Neuroscience 2.3k
- Computer Vision and Pattern Recognition 757
- Experimental and Cognitive Psychology 407
- Social Psychology 236
- Sensory Systems 203
Countries citing papers authored by Michèle Fabre‐Thorpe
This map shows the geographic impact of Michèle Fabre‐Thorpe'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 Michèle Fabre‐Thorpe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michèle Fabre‐Thorpe more than expected).
Fields of papers citing papers by Michèle Fabre‐Thorpe
This network shows the impact of papers produced by Michèle Fabre‐Thorpe. 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 Michèle Fabre‐Thorpe. The network helps show where Michèle Fabre‐Thorpe may publish in the future.
Co-authorship network of co-authors of Michèle Fabre‐Thorpe
This figure shows the co-authorship network connecting the top 25 collaborators of Michèle Fabre‐Thorpe. A scholar is included among the top collaborators of Michèle Fabre‐Thorpe based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Michèle Fabre‐Thorpe. Michèle Fabre‐Thorpe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 30 | |
| 3 | 45 | |
| 4 | 139 | |
| 5 | 113 | |
| 6 | 25 | |
| 7 | 201 | |
| 8 | 25 | |
| 9 | 117 | |
| 10 | 16 | |
| 11 | 74 | |
| 12 | 19 | |
| 13 | 253 | |
| 14 | 160 | |
| 15 | 39 | |
| 16 | 153 | |
| 17 | 18 | |
| 18 | 6 | |
| 19 | 5 | |
| 20 | 5 |
About Michèle Fabre‐Thorpe
Michèle Fabre‐Thorpe is a scholar working on Cognitive Neuroscience, Sensory Systems and Computer Vision and Pattern Recognition, having authored 41 papers that have together received 2.7k indexed citations. Recurring topics across this work include Face Recognition and Perception (29 papers), Visual perception and processing mechanisms (20 papers) and Neural dynamics and brain function (16 papers). The work is most often cited by research in Cognitive Neuroscience (2.3k citations), Sensory Systems (203 citations) and Computer Vision and Pattern Recognition (757 citations). Michèle Fabre‐Thorpe has collaborated with scholars based in France, Germany and Canada. Frequent co-authors include Simon J. Thorpe, Guillaume A. Rousselet, Marc J.‐M. Macé, O. Joubert, Arnaud Delorme, Denis Fize, Ghislaine Richard, Nadège Bacon-Macé, Karl R. Gegenfurtner and HH Bülthoff. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nature Neuroscience and PLoS ONE.
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.