End-to-end machine learning for experimental physics: using simulated data to train a neural network for object detection in video microscopy
Author:
Affiliation:
1. Department of Physics and Soft Materials Research Center, University of Colorado, Boulder
2. Colorado
3. USA
Abstract
We demonstrate a method for training a convolutional neural network with simulated images for usage on real-world experimental data.
Funder
National Science Foundation
National Aeronautics and Space Administration
Publisher
Royal Society of Chemistry (RSC)
Subject
Condensed Matter Physics,General Chemistry
Link
http://pubs.rsc.org/en/content/articlepdf/2020/SM/C9SM01979K
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