Processing Laue Microdiffraction Raster Scanning Patterns with Machine Learning Algorithms: A Case Study with a Fatigued Polycrystalline Sample

The massive amount of diffraction images collected in a raster scan of Laue microdiffraction calls for a fast treatment with little if any human intervention. The conventional method that has to index diffraction patterns one-by-one is laborious and can hardly give real-time feedback. In this work,...

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Detalles Bibliográficos
Autores principales: Rong, Peng, Zhang, Fengguo, Yang, Qing, Chen, Han, Shi, Qiwei, Zhong, Shengyi, Chen, Zhe, Wang, Haowei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877650/
https://www.ncbi.nlm.nih.gov/pubmed/35208042
http://dx.doi.org/10.3390/ma15041502

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8877650/
https://www.ncbi.nlm.nih.gov/pubmed/35208042
http://dx.doi.org/10.3390/ma15041502

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