Publications
Articles, conférences et chapitres d’ouvrages, de 2018 à 2026.
Les références de 2020 à 2026 viennent de Google Scholar, doublons retirés. Le lien PDF renvoie vers HAL ou arXiv quand le texte est en accès libre.
2026
- Cindy Delage, Stéphane Canu, Marc Décombas, Jonathan Foureur : Statutory AI: Aligning Large Language Models With Legal Norms for Harmlessness. International Conference on Artificial Intelligence for Digital Transformations (AIDT 2026). PDF
2024
- Jordan Patracone, Lucas Anquetil, Yuan Liu, Gilles Gasso, Stéphane Canu : Linear Modeling of the Adversarial Noise Space. ECML PKDD 2024. PDF
- Jordan Patracone, Paul Viallard, Emilie Morvant, Gilles Gasso, Amaury Habrard, Stéphane Canu : A Theoretically Grounded Extension of Universal Attacks from the Attacker’s Viewpoint. ECML PKDD 2024. PDF
- Ramzi Ben Mhenni, Mohamed Ibn Khedher, Stéphane Canu : Sparse and invisible adversarial attacks using MIP Optimization. Prépublication (2024). PDF
- Yuan Liu, Stéphane Canu : The data-driven transferable adversarial space. ACML 2024. PDF
2023
- Stéphane Canu, Dominique Fourdrinier : Data based loss estimation of the mean of a spherical distribution with a residual vector. Metrika 86(8), 851-878 (2023). PDF
- Carole Le Guyader, Samia Ainouz, Stéphane Canu : A physically admissible Stokes vector reconstruction in linear polarimetric imaging. Journal of Mathematical Imaging and Vision 65(4), 592-617 (2023). PDF
- Massih-Reza Amini, Stéphane Canu, Asja Fischer, Tias Guns, Petra Kralj Novak, Grigorios Tsoumakas (éditeurs) : Machine Learning and Knowledge Discovery in Databases: European Conference, ECML PKDD 2022, Grenoble, France, September 19–23, 2022, Proceedings, Part IV. Springer Nature (2023).
- Ramzi Ben Mhenni, Mohamed Ibn Khedher, Stéphane Canu : Robustness of Neural Networks Based on MIP Optimization. Prépublication (2023). PDF
- Julien Denize, Jaonary Rabarisoa, Astrid Orcesi, Romain Hérault, Stéphane Canu : Similarity contrastive estimation for self-supervised soft contrastive learning. WACV 2023. PDF
2022
- Fabian Dubourvieux, Romaric Audigier, Angélique Loesch, Samia Ainouz, Stéphane Canu : A formal approach to good practices in pseudo-labeling for unsupervised domain adaptive re-identification. Computer Vision and Image Understanding 223, 103527 (2022). PDF
- Cyprien Ruffino, Rachel Blin, Samia Ainouz, Gilles Gasso, Romain Hérault, Fabrice Mériaudeau, Stéphane Canu : Physically-admissible polarimetric data augmentation for road-scene analysis. Computer Vision and Image Understanding 222, 103495 (2022). PDF
- Tongxue Zhou, Pierre Vera, Stéphane Canu, Su Ruan : Missing data imputation via conditional generator and correlation learning for multimodal brain tumor segmentation. Pattern Recognition Letters 158, 125-132 (2022). PDF
- Tongxue Zhou, Su Ruan, Pierre Vera, Stéphane Canu : A tri-attention fusion guided multi-modal segmentation network. Pattern Recognition 124, 108417 (2022). PDF
- Jordan Frecon, Gilles Gasso, Stéphane Canu : Semi-universal adversarial perturbations. TechRxiv 2022.
- Jordan Frecon, Lucas Anquetil, Yuan Liu, Gilles Gasso, Stéphane Canu : Adversarial Dictionary Learning. Prépublication (2022). PDF
- A Cifonelli, Stéphane Canu : PES: Probabilistic Exponential Smoothing for Time Series Forecasting. Prépublication (2022).
2021
- Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan : Feature-enhanced generation and multi-modality fusion based deep neural network for brain tumor segmentation with missing MR modalities. Neurocomputing 466, 102-112 (2021). PDF
- Fabian Dubourvieux, Angélique Loesch, Romaric Audigier, Samia Ainouz, Stéphane Canu : Improving unsupervised domain adaptive re-identification via source-guided selection of pseudo-labeling hyperparameters. IEEE Access (2021). PDF
- Rachel Blin, Samia Ainouz, Stéphane Canu, Fabrice Mériaudeau : Multimodal polarimetric and color fusion for road scene analysis in adverse weather conditions. ICIP 2021, 3338-3342.
- Ruobing Shen, Bo Tang, Leo Liberti, Claudia d'Ambrosio, Stéphane Canu : Learning discontinuous piecewise affine fitting functions using mixed integer programming over lattice. Journal of Global Optimization 81(1), 85-108 (2021). PDF
- Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan : A dual supervision guided attentional network for multimodal MR brain tumor segmentation. International Conference on Medical Imaging and Computer-Aided Diagnosis, 3-11 (2021).
- Rachel Blin, Samia Ainouz, Stéphane Canu, Fabrice Mériaudeau : The PolarLITIS dataset: Road scenes under fog. IEEE Transactions on Intelligent Transportation Systems 23(8), 10753-10762 (2021).
- M Jammal, Stéphane Canu, M Abdallah : Joint outlier detection and variable selection using discrete optimization. SORT 45(1), 47-66 (2021).
- Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan : Latent correlation representation learning for brain tumor segmentation with missing MRI modalities. IEEE Transactions on Image Processing 30, 4263-4274 (2021). PDF
- Yi-Shuai Niu, Wentao Ding, Junpeng Hu, Wenxu Xu, Stéphane Canu : Spatio-temporal neural network for fitting and forecasting COVID-19. arXiv:2103.11860 (2021). PDF
- Tongxue Zhou, Stéphane Canu, Su Ruan : Automatic COVID-19 CT segmentation using U-Net integrated spatial and channel attention mechanism. International Journal of Imaging Systems and Technology 31(1), 16-27 (2021).
- Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan : 3D medical multi-modal segmentation network guided by multi-source correlation constraint. ICPR 2020, 10243-10250 (2021).
- Fabian Dubourvieux, Romaric Audigier, Angélique Loesch, Samia Ainouz, Stéphane Canu : Unsupervised domain adaptation for person re-identification through source-guided pseudo-labeling. ICPR 2020, 4957-4964 (2021). PDF
- Amirhossein Rahbari, Marc Rébillat, Nazih Mechbal, Stéphane Canu : Unsupervised damage clustering in complex aeronautical composite structures monitored by Lamb waves: An inductive approach. Engineering Applications of Artificial Intelligence 97, 104099 (2021). PDF
2020
- Tongxue Zhou, Stéphane Canu, Su Ruan : Fusion based on attention mechanism and context constraint for multi-modal brain tumor segmentation. Computerized Medical Imaging and Graphics 86, 101811 (2020). PDF
- Tongxue Zhou, Stéphane Canu, Pierre Vera, Su Ruan : Brain tumor segmentation with missing modalities via latent multi-source correlation representation. MICCAI 2020. PDF
- M Jammal, Stéphane Canu, M Abdallah : Robust and sparse support vector machines via mixed integer programming. LOD 2020.
- M Jammal, Stéphane Canu, M Abdallah : Regularized Robust and Sparse Linear Modeling Using Discrete Optimization. LOD 2020.
- Mikaël Dusenne, Julien Grosjean, Lina F. Soualmia, Clément Massonnaud, Stéphane Canu, Stéfan J. Darmoni : Exploitation de documents médicaux par les techniques d’embedding: application au typage automatique de documents. Plate-Forme Intelligence Artificielle (PFIA) 2020.
- Rachel Blin, Samia Ainouz, Stéphane Canu, Fabrice Mériaudeau : A new multimodal RGB and polarimetric image dataset for road scenes analysis. CVPR Workshops 2020. PDF
- Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan : Incoherent dictionary learning via mixed-integer programming and hybrid augmented Lagrangian. Digital Signal Processing 101, 102703 (2020). PDF
- Nicolas Ballier, Stéphane Canu, Caroline Petitjean, Gilles Gasso, Carlos Balhana, Theodora Alexopoulou, Thomas Gaillat : Machine learning for learner English: A plea for creating learner data challenges. International Journal of Learner Corpus Research 6(1), 72-103 (2020). PDF
- Tongxue Zhou, Su Ruan, Yu Guo, Stéphane Canu : A multi-modality fusion network based on attention mechanism for brain tumor segmentation. ISBI 2020, 377-380.
- Guillaume Lorre, Jaonary Rabarisoa, Astrid Orcesi, Samia Ainouz-Zemouche, Stéphane Canu : Temporal contrastive pretraining for video action recognition. WACV 2020, 651-659. PDF
2019
- Emeric Dynomant, Stéfan J. Darmoni, Émeline Lejeune, Gaétan Kerdelhué, Jean-Philippe Leroy, Vincent Lequertier, Stéphane Canu, Julien Grosjean : Doc2Vec on the PubMed corpus: study of a new approach to generate related articles. arXiv:1911.11698 (2019). PDF
- Rachel Blin, Samia Ainouz, Stéphane Canu, Fabrice Mériaudeau : Road scenes analysis in adverse weather conditions by polarization-encoded images and adapted deep learning. IEEE Intelligent Transportation Systems Conference (ITSC 2019), 27-32.
- Emeric Dynomant, Romain Lelong, Badisse Dahamna, Clément Massonnaud, Gaétan Kerdelhué, Julien Grosjean, Stéphane Canu, Stéfan J. Darmoni : Word embedding for the French natural language in health care: comparative study. JMIR Medical Informatics 7(3), e12310 (2019). PDF
- Tongxue Zhou, Su Ruan, H Hu, Stéphane Canu : Deep learning model integrating dilated convolution and deep supervision for brain tumor segmentation in multi-parametric MRI. International Workshop on Machine Learning in Medical Imaging (MLMI 2019), 574-582.
- Quentin Debard, Jilles Steeve Dibangoye, Stéphane Canu, Christian Wolf : Learning 3D navigation protocols on touch interfaces with cooperative multi-agent reinforcement learning. ECML PKDD 2019. PDF
- Tongxue Zhou, Su Ruan, Stéphane Canu : A review: Deep learning for medical image segmentation using multi-modality fusion. Array 3, 100004 (2019). PDF
- Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan : Apprentissage de dictionnaire faiblement cohérent par programmation quadratique mixte. 27e Colloque GRETSI sur le traitement du signal et des images (GRETSI 2019). PDF
- Jorge Guevara, Roberto Hirata Jr., Stéphane Canu : Kernels on fuzzy sets: an overview. arXiv:1907.12991 (2019). PDF
- Rachel Blin, Samia Ainouz, Stéphane Canu, Fabrice Mériaudeau : Adapted learning for polarization-based car detection. 14th International Conference on Quality Control by Artificial Vision (QCAV 2019).
- Guillaume Lorre, Jaonary Rabarisoa, Astrid Orcesi, Samia Ainouz, Stéphane Canu : Contrastive predictive coding for video representation learning. ICML 2019 Workshop on Self-Supervised Learning. PDF
- Ismaïla Seck, Gaëlle Loosli, Stéphane Canu : L1-norm double backpropagation adversarial defense. ESANN 2019. PDF
- Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan : Mixed integer programming for sparse coding: Application to image denoising. IEEE Transactions on Computational Imaging 5(3), 354-365 (2019). PDF
2018
- Quentin Debard, Christian Wolf, Stéphane Canu, Julien Arné: Learning to Recognize Touch Gestures: Recurrent vs. Convolutional Features and Dynamic Sampling. FG 2018: 114-121
- Yuan Liu, Stéphane Canu, Paul Honeine, Su Ruan: K-SVD with a Real ℓ0 Optimization: Application to Image Denoising. MLSP 2018: 1-6
Pour les publications plus anciennes, voir HAL, Google Scholar ou DBLP.