Nicolas Boutry
Publications
Publications
|
|
Found in Translation: semantic approaches for enhancing AI interpretability in face verification2025 |
|
|
Bridging Human Concepts and Computer Vision for Explainable Face Verification2024 |
BuyTheDips: PathLoss for improved topology-preserving deep learning-based image segmentation2022 |
|
|
|
A Proof of the Tree of Shapes in n-D2022 |
|
|
Spectral Graph Analysis of Bipartite Graphs for Advanced Attack DetectionEuropean Interdisciplinary Cybersecurity Conference (EICC25), Apr 2025, Rennes, France |
|
|
Spectral Analysis for Attack DetectionRESSI (Rendez-Vous de la Recherche et de l'Enseignement de la Sécurité des Systèmes d'Information), Eppe-Sauvage, France, mai 2024, May 2024, Eppe-Sauvage, France |
|
|
Graph-Based Spectral Analysis for Detecting Cyber Attacks19th International Conference on Availability, Reliability and Security (ARES'24), Jul 2024, Vienne, Austria. pp.23, ⟨10.1145/3664476.3664498⟩ |
Structural and spectral analysis of dynamic graphs for attack detectionPFIA/RJCIA conference, Strasbourg, France, mai 2023, May 2023, Strasbourg, France |
|
|
|
Towards attack detection in traffic data based on spectral graph analysisComplex Computational Ecosystems 2023 (CCE'23), Apr 2023, Bakou, Azerbaïdjan |
Gradients Intégrés RenforcésExplain'AI - EGC Workshop, Jan 2022, Blois, France |
|
An Efficient Cascade of U-Net-like Convolutional Neural Networks devoted to Brain Tumor SegmentationBrainLes 2022: Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, Sep 2022, Singapore, Singapore. pp.149--161, ⟨10.1007/978-3-031-33842-7_13⟩ |
|
Residual 3D U-Net with Localization for Brain Tumor SegmentationInternational MICCAI Brainlesion Workshop, Sep 2021, virtual event, Unknown Region. pp.389--399, ⟨10.1007/978-3-031-08999-2_33⟩ |
|
|
|
Gradient Vector Fields of Discrete Morse Functions and Watershed-cutsDGMM 2022 -- IAPR Second International Conference on Discrete Geometry and Mathematical Morphology, Étienne Baudrier; Benoît Naegel; Adrien Krähenbühl; Mohamed Tajine, Oct 2022, Strasbourg, France. pp.1--13, ⟨10.1007/978-3-031-19897-7_4⟩ |
Topology-Aware Method to Segment 3D Plan Tissue Images36th Conference on Neural Information Processing Systems, AI for Science Workshop, Nov 2022, New Orleans, United States |
|
Visual xAI techniquesEcole Jeunes Chercheuses et Chercheurs en Informatique Mathématique, Maison de la Modélisation, de la Simulation et des Interactions [MSI], Jun 2022, Nice, France |
|
|
|
Introducing the Boundary-Aware loss for deep image segmentationBritish Machine Vision Conference (BMVC) 2021, Nov 2021, Virtual, United Kingdom |
A New Matching Algorithm between Trees of Shapes and its Application to Brain Tumor SegmentationProceedings of the IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM), May 2021, Uppsala, Sweden. pp.67--78, ⟨10.1007/978-3-030-76657-3_4⟩ |
|
FOANet: A Focus of Attention Network with Application to Myocardium SegmentationProceedings of the 25th International Conference on Pattern Recognition (ICPR), Jan 2021, Milan, Italy. pp.1120--1127, ⟨10.1109/ICPR48806.2021.9412016⟩ |
|
Do not Treat Boundaries and Regions Differently: An Example on Heart Left Atrial SegmentationProceedings of the 25th International Conference on Pattern Recognition (ICPR), Jan 2021, Milan, Italy. pp.7447--7453, ⟨10.1109/ICPR48806.2021.9412755⟩ |
|
|
|
An Equivalence Relation between Morphological Dynamics and Persistent Homology in n-DDiscrete Geometry and Mathematical Morphology (DGMM), May 2021, Uppsala, Sweden |
Stability of the Tree of Shapes to Additive NoiseProceedings of the IAPR International Conference on Discrete Geometry and Mathematical Morphology (DGMM), May 2021, Uppsala, Sweden. pp.365--377, ⟨10.1007/978-3-030-76657-3_26⟩ |
|
|
|
Using Separated Inputs for Multimodal Brain Tumor Segmentation with 3D U-Net-like ArchitecturesBrainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries: 5th International Workshop,, Oct 2019, Shenzhen, China. pp.187-199, ⟨10.1007/978-3-030-46640-4_18⟩ |
A Two-Stage Temporal-Like Fully Convolutional Network Framework for Left Ventricle Segmentation and Quantification on MR ImagesStatistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges−-10th International Workshop, STACOM 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 13, 2019, Revised Selected Papers, Oct 2019, Shenzhen, China. pp.405--413, ⟨10.1007/978-3-030-39074-7_42⟩ |
|
Stacked and parallel U-nets with multi-output for myocardial pathology segmentationMyocardial Pathology Segmentation Combining Multi-Sequence CMR Challenge, Dec 2020, Lima, Peru. pp.138--145, ⟨10.1007/978-3-030-65651-5_13⟩ |
|
|
|
A 4D counter-example showing that DWCness does not imply CWCness in n-DCombinatorial Image Analysis. IWCIA 2020, Jul 2020, Novi Sad, Serbia. ⟨10.1007/978-3-030-51002-2_6⟩ |
|
|
Euler Well-ComposednessCombinatorial Image Analysis: Proceedings of the 20th International Workshop (IWCIA 2020), Jul 2020, Novi Sad, Serbia. pp.3--19, ⟨10.1007/978-3-030-51002-2_1⟩ |
|
|
An Equivalence Relation between Morphological Dynamics and Persistent Homology in 1DMathematical Morphology and Its Applications to Signal and Image Processing, Burgeth, Bernhard; Kleefeld, Andreas; Naegel, Benoît; Passat, Nicolas; Perret, Benjamin, 2019, Strasbourg, France. pp.57-68, ⟨10.1007/978-3-030-20867-7_5⟩ |
|
|
One More Step Towards Well-Composedness of Cell Complexes over n-D PicturesProceedings of the 21st International Conference on Discrete Geometry for Computer Imagery (DGCI), Mar 2019, Marne-la-Vallée, France. pp.101--114, ⟨10.1007/978-3-030-14085-4_9⟩ |
|
|
La pseudo-distance du dahuORASIS 2017, GREYC, Jun 2017, Colleville-sur-Mer, France |
|
|
Introducing the Dahu Pseudo-Distance13th International Symposium on Mathematical Morphology (ISMM), May 2017, Fontainebleau, France. ⟨10.1007/978-3-319-57240-6_5⟩ |
|
|
Well-composedness in Alexandrov spaces implies digital well-composedness in Z^n20th IAPR International Conference on Discrete Geometry for Computer Imagery (DGCI), Sep 2017, Vienna, Austria |
|
|
Well-Composedness in Alexandrov Spaces Implies Digital Well-Composedness in $\mathbb {Z}^n$20th International Conference on Discrete Geometry for Computer Imagery (DGCI 2017), Sep 2017, Vienne, Austria. pp.225-237, ⟨10.1007/978-3-319-66272-5_19⟩ |
|
|
How to make nD images Well-composed without interpolationInternational Conference on Image Processing (ICIP), Sep 2015, Quebec City, Canada. ⟨10.1109/ICIP.2015.7351181⟩ |
|
|
How to Make nD Functions Digitally Well-Composed in a Self-dual WayMathematical Morphology and Its Applications to Signal and Image Processing, Benediktsson, J.A.; Chanussot, J.; Najman, L.; Talbot, H., May 2015, Reykjavik, Iceland. pp.561-572, ⟨10.1007/978-3-319-18720-4_47⟩ |
|
|
On making nD images well-composed by a self-dual local interpolation18th IAPR International Conference, DGCI 2014, Sep 2014, Sienna, Italy. pp.320-331, ⟨10.1007/978-3-319-09955-2_27⟩ |
Standardised procedures for ultrasound imaging in paediatric rheumatology: progress of EULAR/PRES task force.Annual European Congress of Rheumatology, EULAR 2018, Jun 2018, Amsterdam, Netherlands. Annals of the Rheumatic Diseases, The EULAR Journal, 77, pp.476 |
|
|
A Study of Well-composedness in n-D.Modeling and Simulation. Université Paris-Est, 2016. English. ⟨NNT : 2016PESC1025⟩ |
|
|
About the equivalence between AWCness and DWCness[Research Report] LIGM - Laboratoire d'Informatique Gaspard-Monge; LRDE - Laboratoire de Recherche et de Développement de l'EPITA. 2016 |