Articles | Volume 9, issue 2
https://doi.org/10.5194/jsss-9-363-2020
https://doi.org/10.5194/jsss-9-363-2020
Regular research article
 | 
02 Nov 2020
Regular research article |  | 02 Nov 2020

Intelligent fault detection of electrical assemblies using hierarchical convolutional networks for supporting automatic optical inspection systems

Alida Ilse Maria Schwebig and Rainer Tutsch

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Latest update: 27 Mar 2024
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Short summary
In order to further increase the performance of neural networks in the field of optical quality assurance of soldered joints, a hierarchical classifier can be used instead of a single network. The global expansion of the classifier enables the inspection task to be distributed over several subnetworks, which results in higher accuracy. Since the individual sub-models only concentrate on the identification of certain characteristics, categorical problems can be solved more effectively.