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Automated detection and segmentation of bacteriocytes from light microscopy images

• Authors : Hutin, Nathan; Lopes, Mélanie, Ribeiro; Gaget, Karen ...

Subjects: [INFO]Computer Science [cs]; [SDV]Life Sciences [q-bio]Nice; FranceNice, France

• Source: Colloque d'Intelligence Artificielle en Imagerie Biomédical (IABM) ; https://hal.science/hal-05109817 ; Colloque d'Intelligence Artificielle en Imagerie Biomédical (IABM), Mar 2025, Nice, France

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Deformation mapping in Lorentz transmission electron microscopy images of magnetic skyrmion lattices

• Authors : Denneulin Thibaud; Kovács András; Dunin-Borkowski Rafal E.

Subjects: skyrmions; fresnel; deformations

• Source: BIO Web of Conferences, Vol 129, p 29010 (2024)

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Deep Learning Style Transfer for Elastic Image Registration of Visually Distinct Correlative Microscopy Images

• Authors : Čermák Jan; Materna Jiří; Ambrož Ondřej

Subjects: correlative-microscopy; image-registration; deep-learning

• Source: BIO Web of Conferences, Vol 129, p 13008 (2024)

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Measuring the Interpretability of High-Resolution Transmission Electron Microscopy Images

• Authors : Lomholdt William Bang; Larsen Matthew Helmi Leth; Valencia Cuauhtémoc Núñez

Subjects: nanopareticles; tem; interpretability

• Source: BIO Web of Conferences, Vol 129, p 26003 (2024)

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Comparative Analysis of Self-Supervised Learning Techniques for Electron Microscopy Images

• Authors : Kazimi Bashir; Sandfeld Stefan

Subjects: self-supervised-learning; electron-microscopy; image-classification

• Source: BIO Web of Conferences, Vol 129, p 10037 (2024)

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Atomistic Simulations in Surface Chemistry to Interpret Scanning Probe Microscopy Images: A Short Review

• Authors : Tiziana Musso

Subjects: Afm; Dft; Experiments

• Source: CHIMIA, Vol 73, Iss 4 (2019)

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Segmentation of cellular microscopy images by Deep Learning in very unsupervised contexts ; Segmentation d'images de microscopie cellulaire par apprentissage profond dans des contextes très peu supervisés

• Authors : Deleruyelle, Arnaud;

Subjects: Segmentation; Deep Learning; Convolutional neural network

• Source: https://theses.hal.science/tel-04084882 ; Apprentissage [cs.LG]. Université de Lille, 2022. Français. ⟨NNT : 2022ULILB037⟩.

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Segmentation d'images de microscopie cellulaire par apprentissage profond dans des contextes très peu supervisés ; Segmentation of cellular microscopy images by Deep Learning in very unsupervised contexts

• Authors : Deleruyelle, Arnaud;

Subjects: Réseau de neurones convolutif; Segmentations d’images; Segmentation

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segmentation applied to material metrology of electronic microscopy images ; segmentation appliquée à la métrologie de matériaux dans des images de microscopie électronique

• Authors : Baderot, Julien;

Subjects: Transmission electron microscopy; Tree of shapes; Segmentation

• Source: https://theses.hal.science/tel-03256727 ; Traitement du signal et de l'image [eess.SP]. Université Grenoble Alpes [2020-.], 2021. Français. ⟨NNT : 2021GRALT008⟩.

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segmentation appliquée à la métrologie de matériaux dans des images de microscopie électronique ; segmentation applied to material metrology of electronic microscopy images

• Authors : Baderot, Julien;

Subjects: Microscope électronique en transmission; Arbre de formes; Segmentation004; 620

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