Product Quality Prediction in Batch Processes with Small Sample Sizes using Siamese Networks

Deep Learning algorithms usually need a large amount of data. Still, when analysing measurements from manufacturing processes, informative data in sufficient quantities is rather rare, making the task more complex. Therefore, the development of so-called few shot learning algorithms, focusing especially on the analysis of small data sets, is one of the current research topics of the Fraunhofer Cluster of Excellence.