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Joao P C Bertoldo
100%
Libre accès
8
Documents
Affiliations actuelles
- 206
- 301492
- 564132
Identifiants chercheurs
- joaobertoldo
- 0000-0002-9512-772X
- Arxiv : cbertoldo_j_1
- Google Scholar : https://scholar.google.fr/citations?user=wzuuIvsAAAAJ
Domaines de recherche
Informatique [cs]
Intelligence artificielle [cs.AI]
Traitement des images [eess.IV]
Publications
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In situ synchrotron X-ray multimodal experiment to study polycrystal plasticityJournal of Synchrotron Radiation, 2023, 30, pp.379 - 389. ⟨10.1107/S1600577522011705⟩
Article dans une revue
hal-04305405v1
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A modular U-Net for automated segmentation of X-ray tomography images in composite materialsFrontiers in Materials, 2021, 8, pp.761229. ⟨10.21203/rs.3.rs-721240/v1⟩
Article dans une revue
hal-03380106v2
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Visualization for Multivariate Gaussian Anomaly Detection in Images2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oct 2023, Paris, France. ⟨10.1109/IPTA59101.2023.10320060⟩
Communication dans un congrès
hal-04319304v1
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Gaussian Image Anomaly Detection with Greedy Eigencomponent SelectionIEEE/CVF International Conference on Computer Vision, Oct 2023, Paris, France
Communication dans un congrès
hal-04319501v1
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Heuristic Hyperparameter Choice for Image Anomaly Detection2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA), Oct 2023, Paris, France. pp.1-5, ⟨10.1109/IPTA59101.2023.10320035⟩
Communication dans un congrès
hal-04319319v1
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AUPIMO: Redefining Visual Anomaly Detection Benchmarks with High Speed and Low Tolerance2024
Pré-publication, Document de travail
hal-04403770v1
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Adapting the Hypersphere Loss Function from Anomaly Detection to Anomaly Segmentation2023
Pré-publication, Document de travail
hal-04319313v1
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[Reproducibility Report] Explainable Deep One-Class Classification2023
Pré-publication, Document de travail
hal-04319312v1
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