A CNN-Based Method for Quantitative Assessment of Steel Microstructures in Welded Zones

A CNN-Based Method for Quantitative Assessment of Steel Microstructures in Welded Zones

The mechanical performance of metallic components is intrinsically linked to their microstructural features. However, the manual quantification of microconstituents in metallographic images remains a time-consuming and subjective task, often requiring over 15 min per image by a trained expert. To ad...

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Bibliographic Details
Main Authors: Cássio Danelon de Almeida, Thales Tozatto Filgueiras, Moisés Luiz Lagares, Bruno da Silva Macêdo, Camila Martins Saporetti, Matteo Bodini, Leonardo Goliatt
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Fibers
Subjects:
convolutional neural networks
microstructure quantification
low-carbon steel
deep learning
image analysis
Online Access:https://www.mdpi.com/2079-6439/13/5/66
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