Durmaz, Ali RizaAli RizaDurmazPotu, Sai TejaSai TejaPotuRomich, DanielDanielRomichMöller, Johannes J.Johannes J.MöllerNütz, RalfRalfNütz2023-12-142023-12-142023https://publica.fraunhofer.de/handle/publica/457992Up to now, the size of the microscopic crystallites has been assessed by metallographers by way of visual inspection- a subjective and error-prone method. Researchers at the Fraunhofer Institute for Mechanics of Materials IWM, in collaboration with Schaeffler Technologies AG & Co. KG, have developed a deep learning model that enables objective and automated assessment and determination of the grain size.endeep learning modelgrain size determinationartificial IntelligenceUsing deep learning to classify steel materials objectivelyjournal article