46 citations · 75 across the 3 of their papers we have counts for
3 papers
DBCal: Density Based Calibration of classifier predictions for uncertainty quantification
Alex Hagen, Karl Pazdernik, Nicole LaHaye +1
Measurement of uncertainty of predictions from machine learning methods is important across scientific domains and applications. We present, to our knowledge, the first such techni…
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…