Search Results for author: Brian L. DeCost

Found 3 papers, 3 papers with code

Fast classification of small X-ray diffraction datasets using data augmentation and deep neural networks

2 code implementations npj Computational Materials 2019 Felipe Oviedo, Zekun Ren, Shijing Sun, Charles Settens, Zhe Liu, Noor Titan Putri Hartono, Savitha Ramasamy, Brian L. DeCost, Siyu I. P. Tian, Giuseppe Romano, Aaron Gilad Kusne, Tonio Buonassisi

We overcome the scarce data problem intrinsic to novel materials development by coupling a supervised machine learning approach with a model-agnostic, physics-informed data augmentation strategy using simulated data from the Inorganic Crystal Structure Database (ICSD) and experimental data.

BIG-bench Machine Learning Data Augmentation +6

High throughput quantitative metallography for complex microstructures using deep learning: A case study in ultrahigh carbon steel

3 code implementations4 May 2018 Brian L. DeCost, Bo Lei, Toby Francis, Elizabeth A. Holm

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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