A collection of AWESOME things about ML for non-destructive testing

• awesome-NDT
• Contents
• Papers
  • Survey
  • Supervised Learning
    • Classification
    • Regression
    • Object Detection
    • Segmentation
  • Unsupervised Learning
    • Self-Supervised Learning
    • Anomaly Detection
    • Metric Learning
    • Dimension Reduction
  • Image Generation
  • Domain Adaptation
  • Data Augmentation
  • Federated Learning
  • Bayesian inference
  • Simulation
  • Super Resolution
  • denoising technique
  • Physics Informed Neural Network
• Others

• Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review [January 2023]
• Deep learning in automated ultrasonic NDE – Developments, axioms and opportunities [October 2022]
• A review of ultrasonic sensing and machine learning methods to monitor industrial processes [August 2022]
• Artificial Intelligence, Machine Learning and Smart Technologies for Nondestructive Evaluation [May 2022]
• Recent Advances in Machine Learning Applied to Ultrasound Imaging [March 2022]
• A Survey on Artificial Intelligence Research and Its Applications to Non-destructive Evaluation [April 2018]

• Machine Learning and 3D Reconstruction of Materials Surface for Nondestructive Inspection [August 2022]
• Automated detection and characterisation of defects from multiview ultrasonic imaging [June 2022]
• CNN-LSTM network-based damage detection approach for copper pipeline using laser ultrasonic scanning [April 2022]
• TAF2-Net: Triple-Branch Attentive Feature Fusion Network for Ultrasonic Flaw Detection [February 2022]
• A deep learning automatic classification method for clogging pervious pavement [November 2021]
• Automated Flaw Detection in Multi-channel Phased Array Ultrasonic Data Using Machine Learning [August 2021]
• Porosity Evaluation of Additively Manufactured Components Using Deep Learning-based Ultrasonic Nondestructive Testing [April 2021]
• Machine Learning-Based Detection Technique for NDT in Industrial Manufacturing [April 2021]
• Deconvolution of ultrasonic signals using a convolutional neural network [March 2021]
• Identification of Grout Sleeve Joint Defect in Prefabricated Structures Using Deep Learning [October 2020]
• Performance enhancement of convolutional neural network for ultrasonic flaw classification by adopting autoencoder [April 2020]
• Machine Learning in Pipeline Inspection: Applications of supervised learning in non-destructive evaluation [June 2019]
• Convolutional neural network for ultrasonic weldment flaw classification in noisy conditions [April 2019]
• Computerized Ultrasonic Imaging Inspection: From Shallow to Deep Learning [October 2018]
• Deep learning based classification of breast tumors with shear-wave elastography [December 2016]
• Automatic Defect Classification in Ultrasonic NDT Using Artificial Intelligence [December 2010]

• Non-destructive evaluating the density and mechanical properties of ancient timber members based on machine learning approach [July 2022]
• Defect sizing in guided wave imaging structural health monitoring using convolutional neural networks [September 2021]

• Defects detection in weld joints based on visual attention and deep learning [January 2023]
• DefectDet: A deep learning architecture for detection of defects with extreme aspect ratios in ultrasonic images [February 2022]
• Towards using convolutional neural network to locate, identify and size defects in phased array ultrasonic testing [August 2021]
• Flaw Detection from Ultrasonic Images using YOLO and SSD [September 2019]
• Generative adversarial network with object detector discriminator for enhanced defect detection on ultrasonic B-scan [Jun 2021]
• Internal Damage Identification of Sandwich Panels With Truss Core Through Dynamic Properties and Deep Learning [September 2020]
• Concrete crack detection and quantification using deep learning and structured light [August 2020]

• Predicting local material thickness from steady-state ultrasonic wavefield measurements using a convolutional neural network [July 2022]
• Two-stage ultrasound image segmentation using U-Net and test time augmentation [April 2020]
• Fine tuning U-Net for ultrasound image segmentation: which layers? [Feb 2020]
• Breast lesion segmentation in ultrasound images with limited annotated data [Jan 2020]

• Deep anomaly detection model for composite inspection in quadratic frequency modulated thermal wave imaging [December 2022]
• Deep learning-based anomaly detection from ultrasonic images [August 2022]
• Autoencoder-based detection of near-surface defects in ultrasonic testing [February 2022]

• Unsupervised deep learning based approach to temperature monitoring in focused ultrasound treatment [May 2022]

• Convolutional feature extraction for process monitoring using ultrasonic sensors [December 2021]
• Application of Deep Learning in Infrared Non-Destructive Testing [May 2019]

• Generating ultrasonic images indistinguishable from real images using Generative Adversarial Networks [February 2022]

• Machine learning and domain adaptation to monitor yoghurt fermentation using ultrasonic measurements [May 2023]
• Transfer learning for process monitoring using reflection-mode ultrasonic sensing [Aug 2021]

• Augmented Ultrasonic Data for Machine Learning [March 2019]
• Flaw Detection in Ultrasonic Data Using Deep Learning [January 2019]

• Domain Adaptation and Federated Learning for Ultrasonic Monitoring of Beer Fermentation [October 2021]

• The use of full-skip ultrasonic data and Bayesian inference for improved characterisation of crack-like defects [July 2021]

• Optimizing hyperparameters of Data-driven simulation-assisted-Physics learned AI (DPAI) model to reduce compounding error [February 2023]
• Simulation trained CNN for accurate embedded crack length, location, and orientation prediction from ultrasound measurements [May 2022]
• Deep Learning for Ultrasonic Crack Characterization in NDE [May 2021]

• Uncertainty quantification in super-resolution guided wave array imaging using a variational Bayesian deep learning approach [January 2023]
• Real-time super-resolution mapping of locally anisotropic grain orientations for ultrasonic non-destructive evaluation of crystalline material [May 2021]

• Ultrasonic signal enhancement for coarse grain materials by machine learning analysis [December 2021]
• Ultrasonic signal denoising based on autoencoder [April 2020]

• Physics-informed neural network for ultrasound nondestructive quantification of surface breaking cracks [May 2020]

• Improvement Possibilities for Nuclear Power Plants Inspections by Adding Deep Learning-based Assistance Algorithms Into a Classic Ultrasound NDE Acquisition and Analysis Software [February 2023]
• Non-destructive testing (NDT) in industry 4.0: A brief review [June 2021]
• Manufacturing Industry DX through Deep Learning Application Technologies —From Non-Destructive Testing to Quality Control— [February 2020]
• A human-centric approach to AI in aviation [February 2020]
• Advanced methods in NDE using machine learning approaches [April 2018]
• Guidebook on non-destructive testing of concrete structures [September 2002]