2 papers
cs.CV2023
Gap and Overlap Detection in Automated Fiber Placement
Assef Ghamisi, Homayoun Najjaran
The identification and correction of manufacturing defects, particularly gaps and overlaps, are crucial for ensuring high-quality composite parts produced through Automated Fiber P…
cs.CV2023
Anomaly Detection in Automated Fibre Placement: Learning with Data Limitations
Assef Ghamisi, Todd Charter, Li Ji +3
Conventional defect detection systems in Automated Fibre Placement (AFP) typically rely on end-to-end supervised learning, necessitating a substantial number of labelled defective…