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

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

Saved in:
Bibliographic Details
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
Series:Discover Materials
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
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://doi.org/10.1007/s43939-025-00323-6

Similar Items