Defect Detection and Classification in Printed Circuit Boards using Convolutional Neural Networks
Author:
Affiliation:
1. Graduate School Program, Technological Institute of the Philippines,Quezon City,Philippines
2. College of Computing Science, Information and Communication Technology, Isabela State University,Cauay an City,Isabela,Philippines
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10211064/10212098/10212195.pdf?arnumber=10212195
Reference12 articles.
1. Efficient Faster R-CNN: Used in PCB Solder Joint Defects and Components Detection
2. Deep Learning-Based Approaches for Text Recognition in PCB Optical Inspection: A Survey
3. Detection of Bare PCB Defects by using Morphology Technique;nadaf;International Journal of Electronics and Communication Engineering,2016
4. Research on PCB defect detection based on SSD
5. Implementation of Machine Vision based Quality Inspection in Production: An Approach for the Accelerated Execution of Case Studies
Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Defect Recognition on Single Layer Bare Printed Circuit Boards for Quality Control and Visual Inspection: A Low-Sample-Size Deep Transfer Learning Approach;2023 9th International Conference on Signal Processing and Intelligent Systems (ICSPIS);2023-12-14
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