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M. Echlin

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#machine learning Preprint Sep 2026

Symmetry-aware super-resolution of crystal orientation maps via invariant latent-space learning

Crystal-orientation maps are physical fields defined only up to crystal symmetry; electron backscatter diffraction (EBSD) resolves them experimentally, but acquisition-time constraints limit spatial resolution. Unlike conventional images, EBSD data lie on the quotient space $\mathrm{SO}(3)/G$, where $G$ is the crystal-...

Umang Garg, Warren Zamudio, M. Echlin et al. · 0 citations
Open access Aug 2026

A Correlative Microscopy Dataset for Multimodal Data Fusion and Image Matching in Materials Science

Gaining understanding of process-structure-property relationships in materials at a mechanistic level relies on correlative microscopy workflows. These workflows, in turn, fundamentally depend on image matching, i.e., a computer vision task with the objective of finding point correspondences in pairs of images. Mat...

A. Durmaz, James D. Lamb, Kamilla Zaripova et al. · 1 citation

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