Industrial X-ray Image Analysis with Deep Neural Networks Robust to Unexpected Input Data

• Published in: Metals (Basel ) Vol. 12; no. 11; p. 1963
• Main Authors: Lindgren, Erik, Zach, Christopher
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.11.2022
• Subjects: Accuracy; Algorithms; Artificial intelligence; Artificial neural networks; Classification; Datasets; Deep learning; Defects; Dictionaries; Fusion welding; Geometry; Hypothesis testing; Image analysis; Image quality; Inspection; Machine learning; Manufacturing; Manufacturing industry; Neural networks; non-destructive evaluation; Production Technology; Produktionsteknik; Quality control; Quality control equipment; Robustness; Training; weld inspection; X ray inspection; X-ray inspection; deep learning; weld inspection; non-destructive evaluation

X-ray inspection is often an essential part of quality control within quality critical manufacturing industries. Within such industries, X-ray image interpretation is resource intensive and typically conducted by humans. An increased level of automatization would be preferable, and recent advances i...