Deep learning in electron microscopy
JM Ede - Machine Learning: Science and Technology, 2021 - iopscience.iop.org
Deep learning is transforming most areas of science and technology, including electron
microscopy. This review paper offers a practical perspective aimed at developers with …
microscopy. This review paper offers a practical perspective aimed at developers with …
Synchrotron big data science
C Wang, U Steiner, A Sepe - Small, 2018 - Wiley Online Library
The rapid development of synchrotrons has massively increased the speed at which
experiments can be performed, while new techniques have increased the amount of raw …
experiments can be performed, while new techniques have increased the amount of raw …
A kriging-based approach to autonomous experimentation with applications to x-ray scattering
Modern scientific instruments are acquiring data at ever-increasing rates, leading to an
exponential increase in the size of data sets. Taking full advantage of these acquisition rates …
exponential increase in the size of data sets. Taking full advantage of these acquisition rates …
Autonomous materials discovery driven by Gaussian process regression with inhomogeneous measurement noise and anisotropic kernels
A majority of experimental disciplines face the challenge of exploring large and high-
dimensional parameter spaces in search of new scientific discoveries. Materials science is …
dimensional parameter spaces in search of new scientific discoveries. Materials science is …
Demonstration of an AI-driven workflow for autonomous high-resolution scanning microscopy
Modern scanning microscopes can image materials with up to sub-atomic spatial and sub-
picosecond time resolutions, but these capabilities come with large volumes of data, which …
picosecond time resolutions, but these capabilities come with large volumes of data, which …
High-throughput mass spectrometry imaging with dynamic sparse sampling
Mass spectrometry imaging (MSI) enables label-free mapping of hundreds of molecules in
biological samples with high sensitivity and unprecedented specificity. Conventional MSI …
biological samples with high sensitivity and unprecedented specificity. Conventional MSI …
Autonomous experiments in scanning probe microscopy and spectroscopy: choosing where to explore polarization dynamics in ferroelectrics
Polarization dynamics in ferroelectric materials are explored via automated experiment in
piezoresponse force microscopy/spectroscopy (PFM/S). A Bayesian optimization (BO) …
piezoresponse force microscopy/spectroscopy (PFM/S). A Bayesian optimization (BO) …
Advances in kriging-based autonomous x-ray scattering experiments
Autonomous experimentation is an emerging paradigm for scientific discovery, wherein
measurement instruments are augmented with decision-making algorithms, allowing them to …
measurement instruments are augmented with decision-making algorithms, allowing them to …
A framework for dynamic image sampling based on supervised learning
Sparse sampling schemes can broadly be classified into two main categories: static
sampling where the sampling pattern is predetermined, and dynamic sampling where each …
sampling where the sampling pattern is predetermined, and dynamic sampling where each …
Dynamic sparse sampling for confocal raman microscopy
The total number of data points required for image generation in Raman microscopy was
greatly reduced using sparse sampling strategies, in which the preceding set of …
greatly reduced using sparse sampling strategies, in which the preceding set of …