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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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- 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
- Publication Do not Treat Boundaries and Regions Differently: An Example on Heart Left Atrial Segmentation in Proceedings of the 25th International Conference on Pattern Recognition (ICPR) — 2 November 2020
- Publication FOANet: A Focus of Attention Network with Application to Myocardium Segmentation in Proceedings of the 25th International Conference on Pattern Recognition (ICPR) — 2 November 2020
- The LRDE is happy to welcome a new member, Caroline Mazini-Rodrigues, who joins the Olena team for her PhD studies. — 21 October 2020
Holding a Master degree in Computer Science from Universidade Estadual de Campinas, Caroline joins LRDE’s Image team where she will focus on Explainability of Convolutional Neural Networks. Her PhD will be conducted in cooperation with Laboratoire d’Informatique Gaspard-Monge.
- Publication Two Stages CNN-Based Segmentation of Gliomas, Uncertainty Quantification and Prediction of Overall Patient Survival in International MICCAI Brainlesion Workshop — 3 September 2020
- Publication Equivalence between Digital Well-Composedness and Well-Composedness in the Sense of Alexandrov on n-D Cubical Grids in Journal of Mathematical Imaging and Vision — 3 September 2020
- Publication Topological Properties of the First Non-Local Digitally Well-Composed Interpolation on n-D Cubical Grids in Journal of Mathematical Imaging and Vision — 3 September 2020