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DTSTART;VALUE=DATE:20221002
DTEND;VALUE=DATE:20221008
DTSTAMP:20260425T212806
CREATED:20220919T093427Z
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UID:6092-1664668800-1665187199@blog.rwth-aachen.de
SUMMARY:Training: Processing and Analyzing Micrographs with Artificial Intelligence
DESCRIPTION:Name: Training: Processing and Analyzing Micrographs with Artificial Intelligence\n \nEvent type: Workshop\n \nDate: October 2 to 7\, 2022\n \nFormat: Hybrid\n \nTarget Audience: HPC users\n \nContact Person: Setareh Medghalchi \n*More information* \n \n\n  \nDesciption  \nHigh performance materials like steels typically possess a heterogeneous microstructure. Owing to this fact\, their properties exceed those of the individual components but collection of image data requires observation and analysis of relatively large areas to capture the heterogeneity reliably. High resolution scanning electron microscopy serves as a tool to unravel many of the physical mechanisms of deformation from the sub-micron to the millimeter scale. On the other hand\, collection\, and analysis of high resolution image data from large areas requires laborious efforts and considerable amount of time\, which is why it is not yet performed routinely. \nHowever\, new image analysis-based tools in conjunction with the application of deep learning convolutional neural networks (CNN) allows us to handle these data collected from large areas. \nIn this workshop\, we will go through several image analysis techniques using python libraries step by step within jupyter notebooks. In this way\, we will introduce the participants to examples of statistical information about specific features of the real microstructures which can be obtained with these methods\, including microstructural information like phase fraction and also insights into deformation mechanisms from damage site detection and classification.
URL:https://blog.rwth-aachen.de/itc-events/en/event/training-processing-and-analyzing-micrographs-with-artificial-intelligence/
LOCATION:Hybrid
CATEGORIES:Einmalig
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