Françoise Dibos

418 total citations
12 papers, 258 citations indexed

About

Françoise Dibos is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Computational Mechanics. According to data from OpenAlex, Françoise Dibos has authored 12 papers receiving a total of 258 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Computer Vision and Pattern Recognition, 4 papers in Media Technology and 2 papers in Computational Mechanics. Recurrent topics in Françoise Dibos's work include Advanced Image Processing Techniques (6 papers), Image and Signal Denoising Methods (5 papers) and Advanced Vision and Imaging (5 papers). Françoise Dibos is often cited by papers focused on Advanced Image Processing Techniques (6 papers), Image and Signal Denoising Methods (5 papers) and Advanced Vision and Imaging (5 papers). Françoise Dibos collaborates with scholars based in France, Vietnam and Italy. Françoise Dibos's 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 and has published in prestigious journals such as IEEE Transactions on Image Processing, International Journal of Computer Vision and SIAM Journal on Numerical Analysis.

In The Last Decade

Françoise Dibos

11 papers receiving 235 citations

Peers

Françoise Dibos

CVPR

MT

CM

RNMI

CTM

Georges Koepfler France

J. Shah United States

Miyoun Jung South Korea

Ginmo Chung United States

Evgeny Strekalovskiy Germany

Chen Sagiv Israel

Andreas Langer Germany

Christian Feddern Germany

Valentin De Bortoli France

Maurice Weiler Netherlands

Georges Koepfler France

Françoise Dibos

213 ×1.0

CVPR

51 ×0.7

MT

43 ×1.0

CM

20 ×0.5

RNMI

23 ×0.8

CTM

Citations per year, relative to Françoise Dibos Françoise Dibos (= 1×) peers Georges Koepfler

Countries citing papers authored by Françoise Dibos

Since Specialization

Citations

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

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

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12 of 12 papers shown

1.

Luong, Marie, et al.. (2016). Example-based super-resolution for enhancing spatial resolution of medical images. PubMed. 2016. 457–460. 1 indexed citations

2.

Luong, Marie, et al.. (2014). Novel Example-Based Method for Super-Resolution and Denoising of Medical Images. IEEE Transactions on Image Processing. 23(4). 1882–1895. 109 indexed citations

3.

Luong, Marie, et al.. (2012). An Optimal Weight Method for CT Image Denoising. Electronic Science and Technology. 10(2). 124–129. 15 indexed citations

4.

Luong, Marie, et al.. (2012). Image resolution enhancement by projection onto convex hull. 1–7. 2 indexed citations

5.

Luong, Marie, et al.. (2012). An Optimal Weight Model for Single Image Super-Resolution. 53. 1–8. 2 indexed citations

6.

Dibos, Françoise, et al.. (2004). The Use of Size Functions for Comparison of Shapes Through Differential Invariants. Journal of Mathematical Imaging and Vision. 21(2). 107–118. 17 indexed citations

7.

Dibos, Françoise, et al.. (2004). Displacement Following of Hidden Objects in a Video Sequence. International Journal of Computer Vision. 57(2). 91–105. 6 indexed citations

8.

Gissot, S., J.‐F. Hochedez, Françoise Dibos, et al.. (2003). Extracting the apparent motion from two successive EIT images. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 1(1). 853–856. 5 indexed citations

9.

Dibos, Françoise. (2001). Du groupe projectif au groupe des recalages, une nouvelle modélisation. Comptes Rendus de l Académie des Sciences - Series I - Mathematics. 332(9). 799–804. 2 indexed citations

10.

Dibos, Françoise & Georges Koepfler. (1999). Global Total Variation Minimization. SIAM Journal on Numerical Analysis. 37(2). 646–664. 31 indexed citations

11.

Dibos, Françoise & Georges Koepfler. (1997). Segmentation d'images couleur par méthode variationnelle.

12.

Catté, Francine, Françoise Dibos, & Georges Koepfler. (1995). A Morphological Scheme for Mean Curvature Motion and Applications to Anisotropic Diffusion and Motion of Level Sets. SIAM Journal on Numerical Analysis. 32(6). 1895–1909. 68 indexed citations

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.

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