most citedAutomated Copper Alloy Grain Size Evaluation Using a Deep-learning CNN

5 citations · 5 across the 2 of their papers we have counts for

collaborators
Showing cs.CVShow all

2 papers · 1 filter

cs.CV2022

SolderNet: Towards Trustworthy Visual Inspection of Solder Joints in Electronics Manufacturing Using Explainable Artificial Intelligence

Hayden Gunraj, Paul Guerrier, Sheldon Fernandez +1

In electronics manufacturing, solder joint defects are a common problem affecting a variety of printed circuit board components. To identify and correct solder joint defects, the s…

cs.CV2020★ 5 cited

Automated Copper Alloy Grain Size Evaluation Using a Deep-learning CNN

George S. Baggs, Paul Guerrier, Andrew Loeb +1

Moog Inc. has automated the evaluation of copper (Cu) alloy grain size using a deep-learning convolutional neural network (CNN). The proof-of-concept automated image acquisition an…