Automatic Detection and Identification of Defects by Deep Learning Algorithms from Pulsed Thermography Data

Automatic Detection and Identification of Defects by Deep Learning Algorithms from Pulsed Thermography Data

Infrared thermography (IRT), is one of the most interesting techniques to identify different kinds of defects, such as delamination and damage existing for quality management of material. Objective detection and segmentation algorithms in deep learning have been widely applied in image processing, a...

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Bibliographic Details
Main Authors: Duan, Y. (Author), Fang, Q. (Author), Garrido, I. (Author), Ibarra-Castanedo, C. (Author), Maldague, X. (Author)
Format: Article
Language:English
Published: MDPI 2023
Subjects:
automatic defect identification and segmentation
Automatic defect identification and segmentation
Convolution
convolutional neural network
Convolutional neural network
Convolutional neural networks
Deep learning
Deep-learning non-destructive evaluation
deep-learning non-destructive evaluation (NDE)
Defect identification
Defects
Detection and identifications
Image quality
infrared image processing
Infrared image processing
infrared thermography
Learning algorithms
Learning systems
Non destructive evaluation
Nondestructive examination
pulsed thermography
Pulsed thermography
Quality management
Region-based
Segmentation methods
Semantic Segmentation
Semantics
Thermography (imaging)
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