Pop-In Identification in Nanoindentation Curves with Deep Learning Algorithms

High–speed nanoindentation rapidly generates large datasets, opening the door for advanced data analysis methods such as the resources available in artificial intelligence. The present study addresses the problem of differentiating load–displacement curves presenting pop-in, slope changes, or instab...

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Detalles Bibliográficos
Autores principales: Kossman, Stephania, Bigerelle, Maxence
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625569/
https://www.ncbi.nlm.nih.gov/pubmed/34832424
http://dx.doi.org/10.3390/ma14227027

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8625569/
https://www.ncbi.nlm.nih.gov/pubmed/34832424
http://dx.doi.org/10.3390/ma14227027

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