Classification of Solder Quality in Through-Hole Devices by Convolutional Neural Networks

Solder inspection has an important place in electronic board production. Deep learning methods can be used to control the quality of solders. In this paper, a comparative study on the performance of deep learning methods for the classification of solder quality of through-hole devices is presented. The dataset used contains 7320 pieces of data. Soldering quality will be classified using three different networks based on ResNet, Inception-v4 and Inception-ResNet, which were created in this study. The test results obtained will be compared.