Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
A robust technique for matching two uncalibrated images through the recovery of the unknown epipolar geometry
1995949 citationsRachid Deriche, Olivier Faugeras et al.profile →
Using Canny's criteria to derive a recursively implemented optimal edge detector
Countries citing papers authored by Rachid Deriche
Since
Specialization
Citations
This map shows the geographic impact of Rachid Deriche'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 Rachid Deriche with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rachid Deriche more than expected).
This network shows the impact of papers produced by Rachid Deriche. 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 Rachid Deriche. The network helps show where Rachid Deriche may publish in the future.
Co-authorship network of co-authors of Rachid Deriche
This figure shows the co-authorship network connecting the top 25 collaborators of Rachid Deriche.
A scholar is included among the top collaborators of Rachid Deriche 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 Rachid Deriche. Rachid Deriche is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Deriche, Rachid, et al.. (2014). Non-Negative Spherical Deconvolution (NNSD) for estimation of fiber Orientation Distribution Function in single-/multi-shell diffusion MRI. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
Lenglet, Christophe, Rachid Deriche, & Olivier Faugeras. (2004). Inferring white matter geometry from diffusion tensor MRI: Application to connectivity mapping. Lecture notes in computer science. 3024. 127–140.5 indexed citations
15.
Tschumperlé, David & Rachid Deriche. (2003). Variational Frameworks for DT-MRI Estimation, Regularization and Visualization. 116–121.17 indexed citations
16.
Lenglet, Christophe, Rachid Deriche, & Olivier Faugeras. (2003). Diffusion Tensor Magnetic Resonance Imaging : Brain Connectivity Mapping. HAL (Le Centre pour la Communication Scientifique Directe). 22(2). 135–7.8 indexed citations
17.
Berger, Marie‐Odile, Rachid Deriche, Isabelle Herlin, Jérôme Jaffré, & Jean‐Michel Morel. (1996). ICAOS'96: 12th International Conference On Analysis and Optimization of Systems - Images, Wavelets and PDE's. SPIRE - Sciences Po Institutional REpository. 219. 359.
18.
Robert, Laurent, Rachid Deriche, & Olivier Faugeras. (1992). Dense depth recovery from stereo images. European Conference on Artificial Intelligence. 821–823.13 indexed citations
19.
Monga, Olivier, Rachid Deriche, Grégoire Malandain, & Jean-Pierre Cocquerez. (1990). 3-D edge detection by recursive filtering and edge tracking. HAL (Le Centre pour la Communication Scientifique Directe).1 indexed citations
20.
Deriche, Rachid, et al.. (1988). 3D Motion Estimation using a Token Tracker.. Machine Vision and Applications. 257–261.7 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.