Why Is Deep Learning Challenging for Printed Circuit Board (PCB) Component Recognition and How Can We Address It?
a) it is an original missing hole defect in the image; (b) random crop... | Download Scientific Diagram
![PDF] FICS-PCB: A Multi-Modal Image Dataset for Automated Printed Circuit Board Visual Inspection | Semantic Scholar PDF] FICS-PCB: A Multi-Modal Image Dataset for Automated Printed Circuit Board Visual Inspection | Semantic Scholar](https://d3i71xaburhd42.cloudfront.net/de274e9ba67a09e80816b98818dcd2debe10350d/1-Figure1-1.png)
PDF] FICS-PCB: A Multi-Modal Image Dataset for Automated Printed Circuit Board Visual Inspection | Semantic Scholar
![Cryptography | Free Full-Text | Why Is Deep Learning Challenging for Printed Circuit Board (PCB) Component Recognition and How Can We Address It? | HTML Cryptography | Free Full-Text | Why Is Deep Learning Challenging for Printed Circuit Board (PCB) Component Recognition and How Can We Address It? | HTML](https://www.mdpi.com/cryptography/cryptography-05-00009/article_deploy/html/images/cryptography-05-00009-g005.png)
Cryptography | Free Full-Text | Why Is Deep Learning Challenging for Printed Circuit Board (PCB) Component Recognition and How Can We Address It? | HTML
![Strongest feature points of the detected missing component based on... | Download Scientific Diagram Strongest feature points of the detected missing component based on... | Download Scientific Diagram](https://www.researchgate.net/publication/336488400/figure/fig9/AS:941748213788710@1601541679915/Strongest-feature-points-of-the-detected-missing-component-based-on-SURF-algorithm.png)
Strongest feature points of the detected missing component based on... | Download Scientific Diagram
![JSSS - Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems JSSS - Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems](https://jsss.copernicus.org/articles/9/363/2020/jsss-9-363-2020-f03-web.png)
JSSS - Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems
![Sensors | Free Full-Text | Printed Circuit Board Defect Detection Using Deep Learning via A Skip-Connected Convolutional Autoencoder | HTML Sensors | Free Full-Text | Printed Circuit Board Defect Detection Using Deep Learning via A Skip-Connected Convolutional Autoencoder | HTML](https://www.mdpi.com/sensors/sensors-21-04968/article_deploy/html/images/sensors-21-04968-g008.png)
Sensors | Free Full-Text | Printed Circuit Board Defect Detection Using Deep Learning via A Skip-Connected Convolutional Autoencoder | HTML
![Defect Detection in Printed Circuit Boards with Pre-Trained Feature Extraction Methodology with Convolution Neural Networks Defect Detection in Printed Circuit Boards with Pre-Trained Feature Extraction Methodology with Convolution Neural Networks](https://file.techscience.com/ueditor/files/cmc/TSP_CMC_70-1/TSP_CMC_19527/TSP_CMC_19527/Images/CMC_19527-fig-1.png)