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Optimal Transport as a Defense Against Adversarial Attacks.

, , и . ICPR, стр. 5044-5051. IEEE, (2020)

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Albrecht Quentin

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Quentin Alamélou

Quentin Monnet

Quentin Bramas

 

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Optimal Transport as a Defense Against Adversarial Attacks., , и . ICPR, стр. 5044-5051. IEEE, (2020)Vulnerability of Person Re-Identification Models to Metric Adversarial Attacks., , и . CVPR Workshops, стр. 3450-3459. Computer Vision Foundation / IEEE, (2020)Improving Few-Shot Learning Through Multi-task Representation Learning Theory., , , , и . ECCV (20), том 13680 из Lecture Notes in Computer Science, стр. 435-452. Springer, (2022)Understanding deep neural networks through the lens of their non-linearity., , , , , , , , и . CoRR, (2023)The Robust Semantic Segmentation UNCV2023 Challenge Results., , , , , , , , , и 27 other автор(ы). ICCV (Workshops), стр. 4620-4630. IEEE, (2023)Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks.. CoRR, (2023)Towards Few-Annotation Learning for Object Detection: Are Transformer-based Models More Efficient?, , , и . WACV, стр. 75-84. IEEE, (2023)Towards Few-Annotation Learning in Computer Vision: Application to Image Classification and Object Detection tasks. (Vers un Apprentissage avec peu d'annotations en Vision par Ordinateur : Application aux tâches de classification d'images et de détection d'objets).. Jean Monnet University, Saint-Étienne, France, (2023)Proposal-Contrastive Pretraining for Object Detection from Fewer Data., , , и . ICLR, OpenReview.net, (2023)Restyling Unsupervised Concept Based Interpretable Networks with Generative Models., , , , и . CoRR, (2024)