109 citations · 193 across the 7 of their papers we have counts for
7 papers
Revealing the Evolution of Order in Materials Microstructures Using Multi-Modal Computer Vision
Arman Ter-Petrosyan, Michael Holden, Jenna A. Bilbrey +11
The development of high-performance materials for microelectronics, energy storage, and extreme environments depends on our ability to describe and direct property-defining microst…
Final Report for CHESS: Cloud, High-Performance Computing, and Edge for Science and Security
Nathan Tallent, Jan Strube, Luanzheng Guo +9
Automating the theory-experiment cycle requires effective distributed workflows that utilize a computing continuum spanning lab instruments, edge sensors, computing resources at mu…
Deep Learning for Automated Experimentation in Scanning Transmission Electron Microscopy
Sergei V. Kalinin, Debangshu Mukherjee, Kevin M. Roccapriore +9
Machine learning (ML) has become critical for post-acquisition data analysis in (scanning) transmission electron microscopy, (S)TEM, imaging and spectroscopy. An emerging trend is…
Evaluating Stage Motion for Automated Electron Microscopy
Kevin R. Fiedler, Matthew Olszta, Kayla Yano +4
Precise control is an essential and elusive quality of emerging self-driving microscopes. It is widely understood these instruments must be capable of performing rapid, high-volume…
An Automated Scanning Transmission Electron Microscope Guided by Sparse Data Analytics
Matthew Olszta, Derek Hopkins, Kevin R. Fiedler +3
Artificial intelligence (AI) promises to reshape scientific inquiry and enable breakthrough discoveries in areas such as energy storage, quantum computing, and biomedicine. Scannin…
Design of a Graphical User Interface for Few-Shot Machine Learning Classification of Electron Microscopy Data
Christina Doty, Shaun Gallagher, Wenqi Cui +5
The recent growth in data volumes produced by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine lea…
A Topological-Framework to Improve Analysis of Machine Learning Model Performance
Henry Kvinge, Colby Wight, Sarah Akers +7
As both machine learning models and the datasets on which they are evaluated have grown in size and complexity, the practice of using a few summary statistics to understand model p…