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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Vydáno v:	Infrared physics & technology Ročník 143; s. 105612
Hlavní autoři:	Yerneni, Naga Prasanthi, Ghali, V.S., Vesala, G.T., Wang, Fei, Mulaveesala, Ravibabu
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.12.2024
Témata:	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
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