A PCB Soldering Joint Defect Recognition System Using Convolutional Neural Network-Reference-Cited by-同舟云学术

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A PCB Soldering Joint Defect Recognition System Using Convolutional Neural Network

Published:2021-11-27 Issue: Volume: Page:
ISSN:
Container-title:2021 Innovations in Power and Advanced Computing Technologies (i-PACT)
language:
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Author:

Tai Kar Wai¹,Chuah Joon Huang²,Leong Hungyang¹,Kamarudin Nazhatul Hafizah¹

Affiliation:

1. UCSI University,Faculty of Engineering Technology and Built Environment,Department of Electrical and Electronic Engineering,Kuala Lumpur,Malaysia

2. University of Malaya,Faculty of Engineering,Department of Electrical Engineering,Kuala Lumpur,Malaysia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9696358/9696444/09696857.pdf?arnumber=9696857

Reference20 articles.

1. Solder Joint Defect Detection in the Connectors Using Improved Faster-RCNN Algorithm

2. Soldering defect detection in automatic optical inspection

3. Solder joint defect classification based on ensemble learning

4. Two-stage Soldering Defect Detection with Deep Learning;ye;KTH - Royal Institute of Technology,2019

5. SMD Defect Classification by Convolution Neural Network and PCB Image Transform

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. Research on PCB defect detection using artificial intelligence: a systematic mapping study;Evolutionary Intelligence;2024-04-02

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