74 citations · 102 across the 4 of their papers we have counts for
4 papers
A robust synthetic data generation framework for machine learning in High-Resolution Transmission Electron Microscopy (HRTEM)
Luis Rangel DaCosta, Katherine Sytwu, Catherine Groschner +1
Machine learning techniques are attractive options for developing highly-accurate automated analysis tools for nanomaterials characterization, including high-resolution transmissio…
Understanding the Influence of Receptive Field and Network Complexity in Neural-Network-Guided TEM Image Analysis
Katherine Sytwu, Catherine Groschner, Mary C. Scott
Trained neural networks are promising tools to analyze the ever-increasing amount of scientific image data, but it is unclear how to best customize these networks for the unique fe…
Simultaneous Successive Twinning Captured by Atomic Electron Tomography
Phillip M. Pelz, Catherine K. Groschner, Alexandra Bruefach +3
Shape-controlled synthesis of multiply twinned nanostructures is heavily emphasized in nanoscience, in large part due to the desire to control the size, shape, and terminating face…
Machine Learning Pipeline for Segmentation and Defect Identification from High Resolution Transmission Electron Microscopy Data
C. K. Groschner, Christina Choi, M. C. Scott
In the field of transmission electron microscopy, data interpretation often lags behind acquisition methods, as image processing methods often have to be manually tailored to indiv…