Automatic Defects Segmentation and Identification by Deep Learning Algorithm with Pulsed Thermography: Synthetic and Experimental Data

Automatic Defects Segmentation and Identification by Deep Learning Algorithm with Pulsed Thermography: Synthetic and Experimental Data

In quality evaluation (QE) of the industrial production field, infrared thermography (IRT) is one of the most crucial techniques used for evaluating composite materials due to the properties of low cost, fast inspection of large surfaces, and safety. The application of deep neural networks tends to...

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Bibliographic Details
Main Authors: Qiang Fang, Clemente Ibarra-Castanedo, Xavier Maldague
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Big Data and Cognitive Computing
Subjects:
automatic defect detection
infrared thermography
deep learning algorithms
Non-Destructive Evaluation (NDE)
supervised learning
image processing
Online Access:https://www.mdpi.com/2504-2289/5/1/9

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https://www.mdpi.com/2504-2289/5/1/9

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