Student reports
From LRDE
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Last abstracts : Gitlab
Title | Authors | Year | |
---|---|---|---|
guillet.21.seminar | Brain MRI Segmentation using fully convolutional network | William Guillet | 2023 |
dubois.22.seminar | Fast reductions for ω-automaton | Jérôme Dubois | 2022 |
pape.21.seminar | Polynomial Identification of omega-Language | Corentin Pape | 2021 |
habib.21.seminar | Building a quantum perceptron | Nathan Habib | 2021 |
hermary.21.seminar | Integration of Morphological Operators in Neural Networks | Romain Hermary | 2021 |
gasnault.21.seminar | Brain MRI segmentation using mathematical morphology | Louis Gasnault | 2021 |
dubois.21.seminar | Fast simulation based reduction for ω-automaton | Jérôme Dubois | 2021 |
simonin.21.seminar | Efficient implementations of hierarchical morphological representations | Victor Simonin | 2021 |
buatois.21.seminar | Smart and robust segmentation of medical images using neural networks | Thibault Buatois | 2021 |
fages.21.seminar | Active Learning on Visibly One Counter Systems | Aymeric FAGES | 2021 |
oueslati.21.seminar | genus.py: a Simple Embeddable Type System for the Python language | Mehdi OUESLATI | 2021 |
mom.21.seminar | Real Time Face Expression Recognition | Ferdinand Mom | 2021 |
moreau.21.seminar | Handling blackbox transitions in go2pins | Hugo Moreau | 2021 |
ginane.20.seminar | Detecting danger in marine environment: Part 1 - Making the dataset | Charles Ginane | 2020 |
buatois.20.seminar | Smart and robust segmentation of medical images using neural networks | Thibault Buatois | 2020 |
linsenmaier.20.seminar | Identifying Botnets in the Network using Gaussian Mixture Models | Hugo Linsenmaier | 2020 |
rabier.20.seminar | Loss functions benchmark for brain tumour segmentation | Lukas Rabier | 2020 |
sainson.20.seminar | Detecting Botnets Behaviors over Network Flows using Hidden Markov Models | Antoine Sainson | 2020 |
fages.20.seminar | Verifying Properties on a Program Using Static Analysis and Model Checking | Aymeric Fages | 2020 |
carvalho.20.seminar | Model classification in model checking using random forest | Thomas De Carvalho | 2020 |