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Showing 1–5 of 5 results
Advanced filters: Author: Benjamin Midtvedt Clear advanced filters

  • Object detection using machine learning universally requires vast amounts of training datasets. Midtvedt et al. proposes a deep-learning method that enables detecting microscopic objects with sub-pixel accuracy from a single unlabeled image by exploiting the roto-translational symmetries of the problem.

    • Benjamin Midtvedt
    • Jesús Pineda
    • Giovanni Volpe
    ResearchOpen Access
    Nature Communications
    Volume: 13, P: 1-13

  • Despite recent improvements in microscopy acquisition methods, extracting quantitative information from biological experiments in crowded conditions is a challenging task. Pineda and colleagues propose a geometric deep-learning-based framework for automated trajectory linking and dynamical property estimation that is able to effectively deal with complex biological scenarios.

    • Jesús Pineda
    • Benjamin Midtvedt
    • Carlo Manzo
    ResearchOpen Access
    Nature Machine Intelligence
    Volume: 5, P: 71-82

  • Muñoz-Gil and colleagues report the results of an open challenge where they benchmarked algorithms for the characterization of motion changes in single-particle tracking. By ranking methods on simulations, the competition revealed strengths and limitations of AI and classic approaches, guiding researchers toward optimal tools.

    • Gorka Muñoz-Gil
    • Harshith Bachimanchi
    • Carlo Manzo
    ResearchOpen Access
    Nature Communications
    Volume: 16, P: 1-17

  • Recent advances in manipulating microscopic objects involve utilizing critical Casimir forces, controllable via temperature and chemical properties. By demonstrating the efficiency of critical Casimir torques, the authors enable precise alignment of microscopic objects on nanopatterned substrates.

    • Gan Wang
    • Piotr Nowakowski
    • Giovanni Volpe
    ResearchOpen Access
    Nature Communications
    Volume: 15, P: 1-10

  • Active matter can spontaneously form complex patterns and assemblies via a one-way energy flow from the environment into the system. Here, the authors demonstrate that a two-way coupling, where active particles act back on the environment can give rise to novel superstructures, named as active droploids.

    • Jens Grauer
    • Falko Schmidt
    • Benno Liebchen
    ResearchOpen Access
    Nature Communications
    Volume: 12, P: 1-8