Advancing PCB Assurance Towards Netlist Extraction with the Integration of X-Ray Imaging and Semi-Supervised Learning Techniques
PCBs are indispensable components that enable the functionality of modern electronics across numerous industries. This study presents a framework for their semi-supervised netlist extraction by addressing the challenges during X-ray tomography. Leveraging AI models during annotation saves time while allowing SMEs to fix AI-generated errors.
Authors
- Patrick Craig (ORCID: https://orcid.org/0000-0002-1047-1987)
- Nitin Varshney
- Navid Asadizanjani (ORCID: https://orcid.org/0000-0003-3347-5072)
- Antika Roy (ORCID: https://orcid.org/0000-0001-7954-5588)
Institutions
- University of Florida (US)
Publication Details
- Published
- 2024-08-14
- DOI
- https://doi.org/10.1109/rapid60772.2024.10647049
- Citations
- 3
- Primary Topic
- Industrial Vision Systems and Defect Detection
- Type
- article
- Field-Weighted Citation Impact
- 1.05