62 citations
- IRT M2PFR9 papers
- Institut de Mathématiques de ToulouseFR5 papers
- Institut Polytechnique de BordeauxFR5 papers
- Université Toulouse III - Paul SabatierFR5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Institut de Recherche en Informatique de ToulouseFR4 papers
- Institut National des Sciences Appliquées de ToulouseFR4 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR4 papers
- Université Paris-SaclayFR4 papers
- Université Toulouse-I-CapitoleFR4 papers
- Université Toulouse - Jean JaurèsFR4 papers
- Airbus (France)FR3 papers
32 papers
GNSS Jamming Detection with Automatic Gain Control (AGC) and Carrier-to-Noise Ratio Density (CNO) Observables from a COTS receiver
Syed Ali Kazim, Anas Darwich, Juliette Marais
As rail transport moves toward higher degrees of automation under initiatives like the R2DATO project [1], accurate and reliable train localization has become essential. Global Sat…
Towards a collaborative digital platform for railway infrastructure projects
Pierre Jehel, Pierre-Étienne Gautier, Judicaël Dehotin +1
The management of railway infrastructure projects can be supported by collaborative digital platforms. A survey was carried out to identify the needs and expectations of the variou…
Fast and Flexible Robustness Certificates for Semantic Segmentation
Thomas Massena, Corentin Friedrich, Franck Mamalet +1
Deep Neural Networks are vulnerable to small perturbations that can drastically alter their predictions for perceptually unchanged inputs. The literature on adversarially robust De…
FusWay: Multimodal hybrid fusion approach. Application to Railway Defect Detection
Alexey Zhukov, Jenny Benois-Pineau, Amira Youssef +3
Multimodal fusion is a multimedia technique that has become popular in the wide range of tasks where image information is accompanied by a signal/audio. The latter may not convey h…
Fast 3D Diffusion for Scalable Granular Media Synthesis
Muhammad Moeeze Hassan, Régis Cottereau, Filippo Gatti +1
Discrete Element Method (DEM) simulations of granular media are computationally intensive, particularly during initialization phases dominated by large displacements and kinetic en…
Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks
Thomas Massena, Léo andéol, Thibaut Boissin +4
Conformal Prediction (CP) has proven to be an effective post-hoc method for improving the trustworthiness of neural networks by providing prediction sets with finite-sample guarant…