Exploring the use of machine learning for interpreting electrochemical impedance spectroscopy data: evaluation of the training dataset size

Title
Exploring the use of machine learning for interpreting electrochemical impedance spectroscopy data: evaluation of the training dataset size
Authors
Keywords
Electrochemical Impedance Spectroscopy (EIS), Corrosion, Machine Learning
Journal
CORROSION SCIENCE
Volume 198, Issue -, Pages 110119
Publisher
Elsevier BV
Online
2022-01-22
DOI
10.1016/j.corsci.2022.110119

Ask authors/readers for more resources

Reprint

Contact the author

Publish scientific posters with Peeref

Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.

Learn More

Become a Peeref-certified reviewer

The Peeref Institute provides free reviewer training that teaches the core competencies of the academic peer review process.

Get Started