78 citations · 171 across the 4 of their papers we have counts for
4 papers
Performance, Successes and Limitations of Deep Learning Semantic Segmentation of Multiple Defects in Transmission Electron Micrographs
Ryan Jacobs, Mingren Shen, Yuhan Liu +10
In this work, we perform semantic segmentation of multiple defect types in electron microscopy images of irradiated FeCrAl alloys using a deep learning Mask Regional Convolutional…
Multi defect detection and analysis of electron microscopy images with deep learning
Mingren Shen, Guanzhao Li, Dongxia Wu +12
Electron microscopy is widely used to explore defects in crystal structures, but human detecting of defects is often time-consuming, error-prone, and unreliable, and is not scalabl…
A Deep Learning Based Automatic Defect Analysis Framework for In-situ TEM Ion Irradiations
Mingren Shen, Guanzhao Li, Dongxia Wu +4
Videos captured using Transmission Electron Microscopy (TEM) can encode details regarding the morphological and temporal evolution of a material by taking snapshots of the microstr…
Assessing Graph-based Deep Learning Models for Predicting Flash Point
Xiaoyu Sun, Nathaniel J. Krakauer, Alexander Politowicz +8
Flash points of organic molecules play an important role in preventing flammability hazards and large databases of measured values exist, although millions of compounds remain unme…