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Dataset . 2023
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Data sources: Datacite
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Using CycleGANs to Generate Realistic STEM Images for Machine Learning

Authors: Chia-Hao Lee; Abid Khan; Pinshane Y. Huang; Bryan K. Clark;

Using CycleGANs to Generate Realistic STEM Images for Machine Learning

Abstract

This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Materials Sciences and Engineering under award number DE-SC0020190, which supported the electron microscopy and related data analysis. This work was carried out in part in the Materials Research Laboratory Central Facilities at the University of Illinois Urbana--Champaign. This research is also part of the Delta research computing project, which is supported by the National Science Foundation (award OCI 2005572), and the State of Illinois. Delta is a joint effort of the University of Illinois Urbana--Champaign and its National Center for Supercomputing Applications.

This data set contains part of the images that were used in the manuscript "Using CycleGANs to Generate Realistic STEM Images for Machine Learning", including experimental, simulated, and CycleGAN-processed monolayer WSe2 images. The acquisition and simulated parameters are publicly available in the manuscript (arXiv:2301.07743).

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This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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