Machine Learning Versus Human-Developed Algorithms in Image Analysis of Microstructures release_mivgmwsxxrerzowwe2ulxjsbsy

Abstract

<jats:title>Abstract</jats:title> Automatic image analysis is nowadays a standard method in quality control of metallic materials, especially in grain size, graphite shape and non-metallic content evaluation. Automatically prepared solutions, based on machine learning, constitute an effective and sufficiently precise tool for classification. Human-developed algorithms, on the other hand, require much more experience in preparation, but allow better control of factors affecting the final result. Both attempts were described and compared.
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