The learning of the precipitates morphological parameters from the composition of nickel-based superalloys
It becomes a common practice to adopt high-throughput experiments on superalloys, which can generate a large amount of data. To address this large amount of data, we designed a machine learning (ML) based model to automate the experimental analysis process. More specifically, we adopted the Unet alg...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-08-01
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| Series: | Materials & Design |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0264127521003002 |