Detection and Classification of Defects on Printed Circuit Board Assembly through Deep Learning
Author:
Affiliation:
1. Technical College of Sofia Technical, University of Sofia,Sofia,Bulgaria
2. Technical University of Sofia,Faculty of Applied Mathematics and Informatics,Sofia,Bulgaria
Funder
Bulgarian National Science Fund
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10612282/10612285/10612667.pdf?arnumber=10612667
Reference15 articles.
1. Using infrared thermal responses for PCBA production tests: Feasibility study
2. A Compact High-Resolution Resonance-Based Capacitive Sensor for Defects Detection on PCBAs
3. PCBA Image Analysis: A Comparison of Visible, Infrared & X-ray Wavelengths
4. PCB Defect Detection Based on Deep Learning Algorithm
5. An Enhanced Detection Method of PCB Defect Based on D-DenseNet (PCBDD-DDNet)
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