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inspection planning, programming, precision data acquisition, complex geometric analysis and reporting. Theory and implementation of inspection methodologies including at least two of: non-contact measurement
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ALMA MATER STUDIORUM - UNIVERSITA' DI BOLOGNA - - DIPARTIMENTO DI INFORMATICA - SCIENZA E INGEGNERIA | Italy | about 1 month ago
Description This research project aims to develop a new artificial intelligence model for dense scene understanding from images, that is, for estimating multiple geometric and physical properties. The key
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, SPM, AFNI, or equivalent Advanced preprocessing: geometric distortion correction, harmonization, registration, longitudinal QC Diffusion MRI (tractography, microstructural models) Functional
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the Manchester BHF CRE: Geometric Deep Learning for Complex Manifolds: Novel deep learning theories, models and architectures to simulate interactions within non-Euclidean, patient-specific cardiovascular
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, public authorities in their decisions and businesses in their strategies. Do you want to know more about LIST? Check our website: https://www.list.lu/ How will you contribute? You will develop a multi
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stresses. While effective, this mechanism relies on energy-consuming and irreversible adhesion. A new and fascinating paradigm has recently emerged: geometric cohesion, the spontaneous emergence
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stresses. While effective, this mechanism relies on energy-consuming and irreversible adhesion. A new and fascinating paradigm has recently emerged: geometric cohesion, the spontaneous emergence
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account of the history of geometric mechanics is given in these slides: https://klasmodin.github.io/assets/pdf/modin-geometric-mechanics-lund-2023.pdf More posts related to our research are available here
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holographic models, and applying them to shed new light on the physics behind black hole horizons and spacetime singularities. Matrix theory is an important approach to non-perturbative string theory in which
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models. Geometric Deep Learning for Structural Synthesis: Leveraging Graph Neural Networks (GNNs) and manifold learning to optimise complex geometries in medical device design and advanced manufacturing