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High throughput quantitative metallography for complex microstructures using deep learning: A case study in ultrahigh carbon steel
We apply a deep convolutional neural network segmentation model to enable novel automated microstructure segmentation applications for complex microstructures typically evaluated manually and subjectively.
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