Semi-supervised machine learning workflow for analysis of nanowire morphologies from transmission electron microscopy images
Semi-supervised machine learning workflow for analysis of nanowire morphologies from transmission electron microscopy images
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DOI:
10.1039/d2dd00066k
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发表时间:
2022-03
期刊:
影响因子:
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通讯作者:
Shizhao Lu;Brian Montz;T. Emrick;A. Jayaraman
中科院分区:
文献类型:
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作者:
Shizhao Lu;Brian Montz;T. Emrick;A. Jayaraman
In the field of materials science, microscopy is the first and often only accessible method for structural characterization. There is a growing interest in the development of machine learning methods...