Lukas Wehinger

DEEP, the machine learning toolchain of Fraunhofer IKS, enables the automation of quality control in production environments, even if the requirements are complex. The technologies FAST and Robuscope, likewise developed by Fraunhofer IKS, are essential components of this solution.

Machine learning (ML) is considered a promising technology for the automation of quality control in production environments, even if the requirements are complex. However, ML approaches require sufficiently large datasets for training of the system, which are often unavailable. The ML toolchain DEEP (Date Efficient Evaluation Platform) from Fraunhofer IKS addresses this challenge.

From medical diagnosis to quality control, visual information is often used to make important decisions. Automating these decisions can relieve the burden on experts and avoid errors. This requires complex AI systems whose development involves large amounts of data, and which are generally unable to make reliable predictions. FAST attempts to provide an answer to these problems: a framework for developing reliable AI systems with little data.