Defect Detection for Printed Circuit Board Assembly Using Deep Learning-Reference-Cited by-同舟云学术

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Defect Detection for Printed Circuit Board Assembly Using Deep Learning

Published:2022-07-14 Issue: Volume: Page:
ISSN:
Container-title:2022 8th International Conference on Control Science and Systems Engineering (ICCSSE)
language:
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Author:

Ren Jing¹,Gabbar Hossam A.²,Huang Xishi³,Saberironaghi Alireza¹

Affiliation:

1. Ontario Tech University,Dept. of Electrical and Computer Engineering,Oshawa,ON,Canada

2. Faculty of Energy Systems and Nuclear Science, Engineering and Applied Science Ontario Tech University,Oshawa,ON,Canada

3. RS Opto Tech Ltd,Suzhou,Jiangsu,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10079708/10079728/10079777.pdf?arnumber=10079777

Reference19 articles.

1. Detection of PCB Surface Defects With Improved Faster-RCNN and Feature Pyramid Network

2. Automatic Industry PCB Board DIP Process Defect Detection System Based on Deep Ensemble Self-Adaption Method

3. EMRA-Net: A Pixel-Wise Network Fusing Local and Global Features for Tiny and Low-Contrast Surface Defect Detection

4. A Method of Defect Detection for Focal Hard Samples PCB Based on Extended FPN Model

5. Automatic Industry PCB Board DIP Process Defect Detection with Deep Ensemble Method

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1. Detecting defects in PCB manufacturing: an exploration using Yolov8 deep learning;International Journal on Interactive Design and Manufacturing (IJIDeM);2024-07-09

2. DepthCrackNet: A Deep Learning Model for Automatic Pavement Crack Detection;Journal of Imaging;2024-04-26

3. Literature Review: Global Criticality Assessment Based on Feature Surrogates at the PCBA Levels;2024 25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE);2024-04-07

4. An Enhanced Detection Method of PCB Defect Based on D-DenseNet (PCBDD-DDNet);Electronics;2023-11-22

5. Defect Detection Methods for Industrial Products Using Deep Learning Techniques: A Review;Algorithms;2023-02-08

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