229 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- IRT M2PFR9 papers
- Centre National de la Recherche ScientifiqueFR7 papers
- Laboratoire de Mécanique et Génie CivilFR6 papers
- Université Montpellier 26 papers
- Institut de Mathématiques de ToulouseFR5 papers
- Institut Polytechnique de BordeauxFR5 papers
- Université de MontpellierFR5 papers
- Université Toulouse III - Paul SabatierFR5 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
38 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…
Robust Vision-Based Runway Detection through Conformal Prediction and Conformal mAP
Alya Zouzou, Léo andéol, Mélanie Ducoffe +1
We explore the use of conformal prediction to provide statistical uncertainty guarantees for runway detection in vision-based landing systems (VLS). Using fine-tuned YOLOv5 and YOL…
Conformal Object Detection by Sequential Risk Control
Léo andéol, Luca Mossina, Adrien Mazoyer +1
Recent advances in object detectors have led to their adoption for industrial uses. However, their deployment in safety-critical applications is hindered by the inherent lack of re…
Improving knowledge of the acoustic factors involved in railway noise annoyance: first results of a pilot field survey of sixty-two local residents
Matthieu Sineau, Manuel Hellot, Robin Mafféïs +4
Railway transportation contributes to the objectives of decarbonization but also generates negative externalities, including noise. Energy noise indicators used to characterize pop…
An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures
Thibaut Boissin, Franck Mamalet, Thomas Fel +3
Orthogonal convolutional layers are valuable components in multiple areas of machine learning, such as adversarial robustness, normalizing flows, GANs, and Lipschitz-constrained mo…
Evaluation of 'Dunkelflaute' event detection methods considering grid operators' needs
Benjamin Biewald, Bastien Cozian, Laurent Dubus +2
Weather conditions associated with low electricity production from renewable energy sources (RES) can result in challenging 'dunkelflaute' events, where 'dunkel' means dark and 'fl…
Quadratic versus Polynomial Unconstrained Binary Models for Quantum Optimization illustrated on Railway Timetabling
Camille Grange, Marion Lavignac, Valentina Pozzoli +1
Quantum Approximate Optimization Algorithm (QAOA) is one of the most short-term promising quantum-classical algorithm to solve unconstrained combinatorial optimization problems. It…
A framework for GNSS-based solutions performance analysis in an ERTMS context
Juliette Marais, Quentin Mayolle, Martin Fasquelle +2
Context Progresses in GNSS-based solution introduction in rail applications GNSS (Global Navigation Satellite System) is now used in most of our travels and each of our smartphone…
Understanding Visual Feature Reliance through the Lens of Complexity
Thomas Fel, Louis Bethune, Andrew Kyle Lampinen +2
Recent studies suggest that deep learning models inductive bias towards favoring simpler features may be one of the sources of shortcut learning. Yet, there has been limited focus…
How to design a dataset compliant with an ML-based system ODD?
Cyril Cappi, Noémie Cohen, Mélanie Ducoffe +8
This paper focuses on a Vision-based Landing task and presents the design and the validation of a dataset that would comply with the Operational Design Domain (ODD) of a Machine-Le…
Out-of-Distribution Detection Should Use Conformal Prediction (and Vice-versa?)
Paul Novello, Joseba Dalmau, Léo Andeol
Research on Out-Of-Distribution (OOD) detection focuses mainly on building scores that efficiently distinguish OOD data from In Distribution (ID) data. On the other hand, Conformal…
A New Hybrid Approach for Identifying Obsolescence Features: Applied to Railway Signaling Infrastructure
Elie Saad, Mariem Besbes, Marc Zolghadri +2
Electrical component obsolescence poses a major issue especially within systems with large life cycles. Thus, finding the optimal management solution for each obsolescence case is…
Human Reliability Assessment method applied to investigate human factors in NDT -- The case of the interpretation of radiograms in the French nuclear sector
Justin Larouze, Etienne Martin, Pierre Calmon
This communication reports on a study carried out in the context of the collaborative FOEHN project (Human and Organizational Factors in Non-Destructive Evaluation) supported by th…
Exact and general decoupled solutions of the LMC Multitask Gaussian Process model
Olivier Truffinet, Karim Ammar, Jean-Philippe Argaud +1
The Linear Model of Co-regionalization (LMC) is a very general multitask gaussian process model for regression or classification. While its expressiveness and conceptual simplicity…
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
Drew Linsley, Pinyuan Feng, Thibaut Boissin +4
Deep neural networks (DNNs) are known to have a fundamental sensitivity to adversarial attacks, perturbations of the input that are imperceptible to humans yet powerful enough to c…
Confident Object Detection via Conformal Prediction and Conformal Risk Control: an Application to Railway Signaling
Léo Andéol, Thomas Fel, Florence De Grancey +1
Deploying deep learning models in real-world certified systems requires the ability to provide confidence estimates that accurately reflect their uncertainty. In this paper, we dem…
An introduction to variational quantum algorithms for combinatorial optimization problems
Camille Grange, Michael Poss, Eric Bourreau
Noisy intermediate-scale quantum computers (NISQ computers) are now readily available, motivating many researchers to experiment with Variational Quantum Algorithms (VQAs). Among t…
Transformers à Grande Vitesse
Farid Arthaud, Guillaume Lecoeur, Alban Pierre
Robust travel time predictions are of prime importance in managing any transportation infrastructure, and particularly in rail networks where they have major impacts both on traffi…
White Paper Machine Learning in Certified Systems
Hervé Delseny, Christophe Gabreau, Adrien Gauffriau +25
Machine Learning (ML) seems to be one of the most promising solution to automate partially or completely some of the complex tasks currently realized by humans, such as driving veh…