A Survey on Automatic Printed Circuit Board Defect Detection Techniques

Author:

Aggarwal Nikhil1,Deshwal Manish1,Samant Piyush2

Affiliation:

1. ECE, Chandigarh University,Punjab,India,140413

2. AIT-CSE, Chandigarh University,Punjab,India,140413

Publisher

IEEE

Reference31 articles.

1. Applying deep learning to defect detection in printed circuit boards via a newest model of you-only-look-once

2. Wavelet-based printed circuit board inspection algorithm

3. An algorithm to group defects on printed circuit board for automated visual inspection;ibrahim;Int J Simul Syst Sci Technol,2008

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

2. Comparative Analysis of Existing Deep Learning Techniques for Automatic Defects Detection in Printed Circuit Boards;2023 3rd International Conference on Technological Advancements in Computational Sciences (ICTACS);2023-11-01

3. Enhancement of Product-Inspection Accuracy Using Convolutional Neural Network and Laplacian Filter to Automate Industrial Manufacturing Processes;Electronics;2023-09-07

4. A Deep Learning-based Microsection Measurement Framework for Print Circuit Boards;2023 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT);2023-07-13

5. Printed Circuit Board Defect Detection Based on Improved YOLOv5;2023 6th International Conference on Information and Computer Technologies (ICICT);2023-03

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