Françoise Dibos
- Computer Vision and Pattern Recognition top 5%
- Media Technology top 5%
- Computational Mechanics
- Radiology, Nuclear Medicine and Imaging
- Computational Theory and Mathematics
- Co-authors
- Georges KoepflerFrancine CattéMarie LuongJean-Marie RocchisaniTruong Q. NguyenPatrizio FrosiniLaurent JacquesD. Berghmans
- Topics
- Advanced Image Processing Techniques (6 papers)Image and Signal Denoising Methods (5 papers)Advanced Vision and Imaging (5 papers)
In The Last Decade
Françoise Dibos
11 papers receiving 235 citations
Peers
Comparison fields: 5 of 49
- Computer Vision and Pattern Recognition 205
- Media Technology 73
- Computational Mechanics 45
- Radiology, Nuclear Medicine and Imaging 37
- Computational Theory and Mathematics 28
Countries citing papers authored by Françoise Dibos
This map shows the geographic impact of Françoise Dibos'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 Françoise Dibos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Françoise Dibos more than expected).
Fields of papers citing papers by Françoise Dibos
This network shows the impact of papers produced by Françoise Dibos. 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 Françoise Dibos. The network helps show where Françoise Dibos may publish in the future.
Co-authorship network of co-authors of Françoise Dibos
This figure shows the co-authorship network connecting the top 25 collaborators of Françoise Dibos. A scholar is included among the top collaborators of Françoise Dibos 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 Françoise Dibos. Françoise Dibos 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 | 109 | |
| 3 | An Optimal Weight Method for CT Image Denoising | 15 |
| 4 | 2 | |
| 5 | 2 | |
| 6 | 17 | |
| 7 | 6 | |
| 8 | Extracting the apparent motion from two successive EIT images | 5 |
| 9 | 2 | |
| 10 | 31 | |
| 11 | Segmentation d'images couleur par méthode variationnelle | 0 |
| 12 | 68 |
About Françoise Dibos
Françoise Dibos is a scholar working on Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition and Media Technology, having authored 12 papers that have together received 258 indexed citations. Recurring topics across this work include Advanced Image Processing Techniques (6 papers), Image and Signal Denoising Methods (5 papers) and Advanced Vision and Imaging (5 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (205 citations), Media Technology (73 citations) and Computational Mechanics (45 citations). Françoise Dibos has collaborated with scholars based in France, Vietnam and Italy. Frequent co-authors include Georges Koepfler, Francine Catté, Marie Luong, Jean-Marie Rocchisani, Truong Q. Nguyen, Patrizio Frosini, Laurent Jacques, D. Berghmans, A. N. Zhukov and S. Gissot. Their work appears in journals such as IEEE Transactions on Image Processing, International Journal of Computer Vision and SIAM Journal on Numerical Analysis.
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.