Interpretable and Explainable Machine Learning for Ultrasonic Defect Sizing-Reference-Cited by-同舟云学术

Interpretable and Explainable Machine Learning for Ultrasonic Defect Sizing

Published:2023-04 Issue:4 Volume:70 Page:277-290
ISSN:0885-3010
Container-title:IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control
language:
Short-container-title:IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

Author:

Pyle Richard J.¹^ORCID,Hughes Robert R.¹^ORCID,Wilcox Paul D.¹^ORCID

Affiliation:

1. Department of Mechanical Engineering, University of Bristol, Bristol, U.K.

Funder

Engineering and Physical Sciences Research Council (EPSRC) through the Research Centre for Non-Destructive Evaluation (RCNDE), with additional funding provided by Baker Hughes, Cramlington, UK

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Acoustics and Ultrasonics,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/58/10084402/10052715.pdf?arnumber=10052715

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