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From LRDE
The LRDE is a research laboratory under the tutelage of EPITA, Graduate School of Computer Science.
Our main areas of expertise are « Image processing and pattern recognition » and « Automata and verification » with a transverse research axis « Performance and genericity ».
Building on its solid scientific production and academic collaborations, the laboratory has industrial contracts, conducts internal research projects and participates in collaborative academic research projects.
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- Publication A New Matching Algorithm between Trees of Shapes and its Application to Brain Tumor Segmentation in Proceedings of the IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM) — 2 March 2021
- Publication An Equivalence Relation between Morphological Dynamics and Persistent Homology in n-D in Proceedings of the IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM) — 2 March 2021
- Publication Deep Learning for Detection and Segmentation of Artefact and Disease Instances in Gastrointestinal Endoscopy in Medical Image Analysis — 24 February 2021
- Publication Combining Deep Learning and Mathematical Morphology for Historical Map Segmentation in IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM) — 16 February 2021
- Publication Going beyond p-convolutions to learn grayscale morphological operators in IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM) — 16 February 2021
- LRDE Seminar on Performance and Genericity - Generating Posets Beyond N — 10 February 2021
by Uli Fahrenberg, Ecole Polytechnique
- LRDE Seminar on Performance and Genericity - Diagnosis and Opacity in Partially Observable Systems — 16 December 2020
by Stefan Schwoon, ENS Paris-Saclay
- The LRDE hosts a new member, Baptiste Esteban, who joins the Olena team for his PhD studies. — 16 November 2020
After completing EPITA's IMAGE and RDI double major, Baptiste is back at LRDE for his PhD. Having worked on noise estimation in natural images with mathematical morphology approaches, he will now focus on how to conciliate genericity and performance of image processing algorithms in dynamic contexts, especially noise estimation as a validation framework.
- Publication A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging in Medical Image Analysis — 10 November 2020
- Publication PAIP 2019: Liver cancer segmentation challenge in Medical Image Analysis — 10 November 2020
