Deep Learning-Driven X-Ray Analysis for High-Throughput Manufacturing
This article introduces a framework for automated defect detection in printed circuit boards for computational X-ray systems. It presents an implementation framework of attentionbased instance segmentation models on a limited number of radiographs from computed laminography and tomography, optimizing for high-speed analysis in manufacturing environments.
Authors
- Patrick Craig (ORCID: https://orcid.org/0000-0002-1047-1987)
- Shajib Ghosh (ORCID: https://orcid.org/0000-0003-3523-8177)
- Nitin Varshney
- Navid Asadizanjani (ORCID: https://orcid.org/0000-0002-7097-4463)
- Antika Roy (ORCID: https://orcid.org/0000-0001-7954-5588)
- Md. Shovon
Institutions
- University of Florida (US)
Publication Details
- Published
- 2025-08-13
- DOI
- https://doi.org/10.1109/rapid64712.2025.11151434
- Primary Topic
- Advanced X-ray and CT Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00