Hybrid machine learning and regression framework for automated phase classification and quantification in SEM images of commercial steels

Abstract This study presents an integrated framework combining supervised classification and composition-driven regression modeling for automated phase identification and quantification in steel microstructures. SEM micrographs of three commercially used steels EN3, EN353, and 20MnCr5 were acquired...

Full description

Bibliographic Details

Published in:	Discover Materials
Main Authors:	Pavan Hiremath, Krishnamurthy D. Ambiger, Shilpa Suresh, Ranjan Kumar Ghadai, Ramakrishna Vikas Sadanand, G. Divya Deepak
Format:	Article
Language:	English
Published:	Springer 2025-08-01
Subjects:	Microstructural phase classification GLCM texture features Random forest classifier Steel microstructures Regression-Based phase prediction
Online Access:	https://doi.org/10.1007/s43939-025-00323-6