Franck Leclerc
About
In The Last Decade
Franck Leclerc
3 papers receiving 382 citations
Peers
Comparison fields: 5 of 37
- Computer Vision and Pattern Recognition 321
- Artificial Intelligence 132
- Cognitive Neuroscience 78
- Media Technology 76
- Human-Computer Interaction 66
Countries citing papers authored by Franck Leclerc
This map shows the geographic impact of Franck Leclerc'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 Franck Leclerc with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Franck Leclerc more than expected).
Fields of papers citing papers by Franck Leclerc
This network shows the impact of papers produced by Franck Leclerc. 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 Franck Leclerc. The network helps show where Franck Leclerc may publish in the future.
Co-authorship network of co-authors of Franck Leclerc
This figure shows the co-authorship network connecting the top 25 collaborators of Franck Leclerc. A scholar is included among the top collaborators of Franck Leclerc 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 Franck Leclerc. Franck Leclerc is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Modèle de génération de mouvements rapides en représentation de signatures manuscrites | 3 |
| 2 | 317 | |
| 3 | 101 |
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.