Printed Circuit Board Defects Detection Based on Oriented Fast and Rotational Brief with Super Resolution

Authors

  • Parvathi R
  • Akash Shiv Janardhan
  • Meenakshi S
  • Shreya Janarthanan

Keywords:

Artificial Intelligence, Machine Learning, Printed Circuit Board, Positive defect, Negative defect, Image segmentation, Defect Classification, Defect Detection, Neural networks.

Abstract

PCBs-Printed Circuit Board with a single defect will cause the board to dysfunction. Checking and assessing the printed circuit board (PCB) is very important in the electronics manufacturing industry to provide quality assurance of the device and durability, slice fabricating cost and to build creation. Just a manual method of review level isn't to the point of actually looking at the nature of PCB. So, there is a requirement for robotized investigation. The PCB review includes discovery of imperfections in the PCB and characterization of those surrenders to recognize the underlying foundations of deformities. In this paper, abandons is recognized and are arranged in all potential classes utilizing a referential review approach.

Downloads

Download data is not yet available.

Downloads

Published

2022-05-03

How to Cite

Parvathi R, Akash Shiv Janardhan, Meenakshi S, & Shreya Janarthanan. (2022). Printed Circuit Board Defects Detection Based on Oriented Fast and Rotational Brief with Super Resolution. International Journal of Progressive Research in Science and Engineering, 3(04), 144–151. Retrieved from https://journal.ijprse.com/index.php/ijprse/article/view/548

Issue

Section

Articles