Nicolas Papadakis
- Computer Vision and Pattern Recognition top 10%
- Applied Mathematics top 10%
- Artificial Intelligence
- Computational Mechanics
- Statistics and Probability top 10%
- Co-authors
- Gabriel PeyréÉdouard OudetSira FerradansJean–François AujolJulien RabinRémi GiraudVinh‐Thong TaJérémie Bigot
- Topics
- Medical Image Segmentation Techniques (4 papers)Advanced Image Fusion Techniques (3 papers)Image Enhancement Techniques (2 papers)
- Journals
- Tellus A Dynamic Meteorology and OceanographySIAM Journal on Mathematical AnalysisSIAM Journal on Imaging Sciences
- Partner nations
- FranceUnited StatesArgentina
In The Last Decade
Nicolas Papadakis
8 papers receiving 206 citations
Peers
Comparison fields: 5 of 59
- Computer Vision and Pattern Recognition 65
- Applied Mathematics 47
- Artificial Intelligence 34
- Computational Mechanics 31
- Statistics and Probability 30
Countries citing papers authored by Nicolas Papadakis
This map shows the geographic impact of Nicolas Papadakis'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 Nicolas Papadakis with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicolas Papadakis more than expected).
Fields of papers citing papers by Nicolas Papadakis
This network shows the impact of papers produced by Nicolas Papadakis. 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 Nicolas Papadakis. The network helps show where Nicolas Papadakis may publish in the future.
Co-authorship network of co-authors of Nicolas Papadakis
This figure shows the co-authorship network connecting the top 25 collaborators of Nicolas Papadakis. A scholar is included among the top collaborators of Nicolas Papadakis 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 Nicolas Papadakis. Nicolas Papadakis is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 9 | |
| 2 | 11 | |
| 3 | 4 | |
| 4 | 7 | |
| 5 | 90 | |
| 6 | 87 | |
| 7 | 2 | |
| 8 | A variational method for joint tracking of curve and motion | 4 |
About Nicolas Papadakis
Nicolas Papadakis is a scholar working on Media Technology, Computer Vision and Pattern Recognition and Applied Mathematics, having authored 8 papers that have together received 214 indexed citations. Recurring topics across this work include Medical Image Segmentation Techniques (4 papers), Advanced Image Fusion Techniques (3 papers) and Image Enhancement Techniques (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (16 citations), Applied Mathematics (47 citations) and Statistics and Probability (30 citations). Nicolas Papadakis has collaborated with scholars based in France, United States and Argentina. Frequent co-authors include Gabriel Peyré, Édouard Oudet, Sira Ferradans, Jean–François Aujol, Julien Rabin, Rémi Giraud, Vinh‐Thong Ta, Jérémie Bigot, Étienne Mémin and Thomas Corpetti. Their work appears in journals such as Tellus A Dynamic Meteorology and Oceanography, SIAM Journal on Mathematical Analysis and SIAM Journal on Imaging Sciences.
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.