Temporal denoising and deep feature learning for enhanced defect detection in thermography using stacked denoising convolution autoencoder

•Temporal denoising of thermal profiles along with deep feature learning for enhanced defect detection in FMTWI is highlighted through a stacked denoising convolution autoencoder.•Adequate data preparation and training strategies enhanced defect signatures.•Temporal signal-to-noise ratio and defect...

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Bibliographic Details

Published in:	Infrared physics & technology Vol. 143; p. 105612
Main Authors:	Yerneni, Naga Prasanthi, Ghali, V.S., Vesala, G.T., Wang, Fei, Mulaveesala, Ravibabu
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.12.2024
Subjects:	CFRP Feature learning Frequency modulated thermography Median filtering Mild steel Signal-to-noise ratio Stacked denoising convolution autoencoder Frequency modulated thermography Mild steel Stacked denoising convolution autoencoder Feature learning Signal-to-noise ratio CFRP Median filtering
ISSN:	1350-4495
Online Access:	Get full text
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